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Outputs (173)

Automated Human-Readable Label Generation in Open Intent Discovery (2024)
Presentation / Conference Contribution
Anderson, G., Hart, E., Gkatzia, D., & Beaver, I. (2024, September). Automated Human-Readable Label Generation in Open Intent Discovery. Presented at Interspeech 2024, Kos, Greece

The correct determination of user intent is key in dialog systems. However, an intent classifier often requires a large, labelled training dataset to identify a set of known intents. The creation of such a dataset is a complex and time-consuming task... Read More about Automated Human-Readable Label Generation in Open Intent Discovery.

Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances (2024)
Presentation / Conference Contribution
Hart, E., Sim, K., & Renau, Q. (2024, September). Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances. Presented at 18th International Conference on Parallel Problem Solving From Nature PPSN 2024, Hagenb

Deep neural networks (DNN) are increasingly being used to perform algorithm-selection in combinatorial optimisation domains, particularly as they accommodate input representations which avoid designing and calculating features. Mounting evidence fro... Read More about Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances.

Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains (2024)
Journal Article
Marrero, A., Segredo, E., Leon, C., & Hart, E. (online). Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains. Evolutionary Computation, https://doi.org/10.1162/evco_a_00350

Gathering sufficient instance data to either train algorithm-selection models or understand algorithm footprints within an instance space can be challenging. We propose an approach to generating synthetic instances that are tailored to perform well w... Read More about Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains.

Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture (2024)
Presentation / Conference Contribution
Le Goff, L., & Hart, E. (2024, July). Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture. Presented at GECCO 2024 Embodied and Evolved Artificial Intelligence Workshop, Melbourne, Australia

Algorithmic frameworks for the joint optimisation of a robot's design and controller often utilise a learning loop nested within an evolutionary algorithm to refine the controller associated with a newly generated robot design. Intuitively, it is rea... Read More about Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture.

An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation (2024)
Presentation / Conference Contribution
Stone, C., Renau, Q., Miguel, I., & Hart, E. (2024, June). An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation. Presented at 18TH LEARNING AND INTELLIGENT OPTIMIZATION CONFERENCE, Ischia Italy

We address the question of multi-task algorithm selection in combinatorial optimisation domains. This is motivated by a desire to simplify the algorithm-selection pipeline by developing a more general classifier that does not require specialised info... Read More about An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation.

On the Utility of Probing Trajectories for Algorithm-Selection (2024)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2024, April). On the Utility of Probing Trajectories for Algorithm-Selection. Presented at EvoStar 2024, Aberystwyth, UK

Machine-learning approaches to algorithm-selection typically take data describing an instance as input. Input data can take the form of features derived from the instance description or fitness landscape , or can be a direct representation of the ins... Read More about On the Utility of Probing Trajectories for Algorithm-Selection.

A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control (2024)
Presentation / Conference Contribution
Montague, K., Hart, E., & Paechter, B. (2024, April). A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. Presented at EvoStar 2024, Aberystwyth

Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an algorithmic perspective, an additional advantage is that extra modules can e... Read More about A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control.

Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution (2024)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2024, July). Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. Presented at ACM GECCO 2024, Melbourne, Australia

The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train machine-learning models for algorithm selection. Quality-Diversity (QD) algorit... Read More about Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution.

Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples (2024)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2024, July). Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples. Presented at GECCO 2024, Melbourne, USA

The choice of input-data used to train algorithm-selection models is recognised as being a critical part of the model success. Recently, feature-free methods for algorithm-selection that use short trajec-tories obtained from running a solver as input... Read More about Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples.

Understanding fitness landscapes in morpho-evolution via local optima networks (2024)
Presentation / Conference Contribution
Thomson, S. L., Le Goff, L., Hart, E., & Buchanan, E. (2024, July). Understanding fitness landscapes in morpho-evolution via local optima networks. Presented at Genetic and Evolutionary Computation Conference (GECCO 2024), Melbourne, Australia

Morpho-Evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and control. Pre... Read More about Understanding fitness landscapes in morpho-evolution via local optima networks.

Generalized Early Stopping in Evolutionary Direct Policy Search (2024)
Journal Article
Arza, E., Le Goff, L. K., & Hart, E. (online). Generalized Early Stopping in Evolutionary Direct Policy Search. ACM Transactions on Evolutionary Learning and Optimization, https://doi.org/10.1145/3653024

Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g. in robotics applications. Often when evaluating solution over a fixe... Read More about Generalized Early Stopping in Evolutionary Direct Policy Search.

Evolving Behavior Allocations in Robot Swarms (2024)
Presentation / Conference Contribution
Hallauer, S., Nitschke, G., & Hart, E. (2023, December). Evolving Behavior Allocations in Robot Swarms. Presented at IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico

Behavioral diversity is known to benefit problem-solving in biological social systems such as insect colonies and human societies, as well as in artificial distributed systems including large-scale software and swarm-robotics systems. We investigate... Read More about Evolving Behavior Allocations in Robot Swarms.

Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces (2023)
Journal Article
Li, W., Buchanan, E., Goff, L. K. L., Hart, E., Hale, M. F., Wei, B., Carlo, M. D., Angus, M., Woolley, R., Gan, Z., Winfield, A. F., Timmis, J., Eiben, A. E., & Tyrrell, A. M. (online). Evaluation of Frameworks That Combine Evolution and Learning to Desi

Jointly optimising both the body and brain of a robot is known to be a challenging task, especially when attempting to evolve designs in simulation that will subsequently be built in the real world. To address this, it is increasingly common to combi... Read More about Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces.

Robotics and Autonomous Systems for Environmental Sustainability: Monitoring Terrestrial Biodiversity (2023)
Preprint / Working Paper
Pringle, S., Davies, Z. G., Goddard, M. A., Dallimer, M., Hart, E., Le Goff, L., & Langdale, S. J. (2023). Robotics and Autonomous Systems for Environmental Sustainability: Monitoring Terrestrial Biodiversity

Welcome to the UK-RAS White paper Series on Robotics and Autonomous Systems (RAS). This is one of the core activities of UK-RAS Network, funded by the Engineering and Physical Sciences Research Council (EPSRC). By Bringing together academic centres o... Read More about Robotics and Autonomous Systems for Environmental Sustainability: Monitoring Terrestrial Biodiversity.

Practical Hardware for Evolvable Robots (2023)
Journal Article
Angus, M., Buchanan, E., Le Goff, L. K., Hart, E., Eiben, A., De Carlo, M., Winfield, A. F., Hale, M., Woolley, R., Timmis, J., & Tyrrell, A. M. (2023). Practical Hardware for Evolvable Robots. Frontiers in Robotics and AI, 10, Article 1206055. https://do

The evolutionary robotics field offers the possibility of autonomously generating robots that are adapted to desired tasks by iteratively optimising across successive generations of robots with varying configurations until a high-performing candidate... Read More about Practical Hardware for Evolvable Robots.

Towards optimisers that `Keep Learning' (2023)
Presentation / Conference Contribution
Hart, E., Miguel, I., Stone, C., & Renau, Q. (2023). Towards optimisers that `Keep Learning'. In GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation (1636-1638). https://doi.org/10.1145/3583133.3596344

We consider optimisation in the context of the need to apply an optimiser to a continual stream of instances from one or more domains, and consider how such a system might 'keep learning': by drawing on past experience to improve performance and lear... Read More about Towards optimisers that `Keep Learning'.

A Feature-Free Approach to Automated Algorithm Selection (2023)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2023). A Feature-Free Approach to Automated Algorithm Selection. In GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation (9-10). https://doi.org/10.1145/3583133.3595832

This article summarises recent work in the domain of feature-free algorithm selection that was published in the Journal of Heuristics in January 2023, with the title 'Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches'. Spec... Read More about A Feature-Free Approach to Automated Algorithm Selection.

Evolving Herding Behaviour Diversity in Robot Swarms (2023)
Presentation / Conference Contribution
Nitschke, G., Hallauer, S., & Hart, E. (2023). Evolving Herding Behaviour Diversity in Robot Swarms. In GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation (95-98). https://doi.org/10.1145/3583133.3590528

Behavioural diversity has been demonstrated as beneficial in biological social systems, such as insect colonies and human societies, as well as artificial systems such as large-scale software and swarm-robotics systems. Evolutionary swarm robotics is... Read More about Evolving Herding Behaviour Diversity in Robot Swarms.

Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space (2023)
Presentation / Conference Contribution
Marrero, A., Segredo, E., Hart, E., Bossek, J., & Neumann, A. (2023). Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space. In GECCO '23: Proceedings of the Genetic and Evolutionary Com

Generating new instances via evolutionary methods is commonly used to create new benchmarking data-sets, with a focus on attempting to cover an instance-space as completely as possible. Recent approaches have exploited Quality-Diversity methods to ev... Read More about Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space.

Learning-Based Neural Ant Colony Optimization (2023)
Presentation / Conference Contribution
Liu, Y., Qiu, J., Hart, E., Yu, Y., Gan, Z., & Li, W. (2023). Learning-Based Neural Ant Colony Optimization. In GECCO 2023: Proceedings of the Genetic and Evolutionary Computation Conference (47-55). https://doi.org/10.1145/3583131.3590483

In this paper, we propose a new ant colony optimization algorithm , called learning-based neural ant colony optimization (LN-ACO), which incorporates an "intelligent ant". This intelligent ant contains a convolutional neural network pre-trained on a... Read More about Learning-Based Neural Ant Colony Optimization.

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Presentation / Conference Contribution
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (2023). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation: 26th Eu

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features (2023)
Presentation / Conference Contribution
Vermetten, D., Wang, H., Sim, K., & Hart, E. (2023, April). To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features. Presented at Evo Applications 2023, Brno, Czech Republic

Dynamic algorithm selection aims to exploit the complementarity of multiple optimization algorithms by switching between them during the search. While these kinds of dynamic algorithms have been shown to have potential to outperform their component a... Read More about To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features.

Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics (2023)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2023, April). Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics. Presented at Evo Applications 2023, Brno, Czech Republic

Quality-diversity (QD) methods such as MAP-Elites have been demonstrated to be useful in the domain of combinatorial optimisation due to their ability to generate a large set of solutions to a single-objective problem that are diverse with respect to... Read More about Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics.

DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains (2023)
Journal Article
Marrero, A., Segredo, E., León, C., & Hart, E. (2023). DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains. SoftwareX, 22, Article 101355. https://doi.org/10.1016/j.softx.2023.101355

To advance research in the development of optimisation algorithms, it is crucial to have access to large test-beds of diverse and discriminatory instances from a domain that can highlight strengths and weaknesses of different algorithms. The DIGNEA t... Read More about DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains.

Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches (2023)
Journal Article
Alissa, M., Sim, K., & Hart, E. (2023). Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches. Journal of Heuristics, 29(1), 1-38. https://doi.org/10.1007/s10732-022-09505-4

We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in online bin-packing. Specifically we train two types of recurrent neural netw... Read More about Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches.

Evolutionary Approaches to Improving the Layouts of Instance-Spaces (2022)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2022, September). Evolutionary Approaches to Improving the Layouts of Instance-Spaces. Presented at 17th International Conference, PPSN 2022, Dortmund, Germany

We propose two new methods for evolving the layout of an instance-space. Specifically we design three different fitness metrics that seek to: (i) reward layouts which place instances won by the same solver close in the space; (ii) reward layouts that... Read More about Evolutionary Approaches to Improving the Layouts of Instance-Spaces.

A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem (2022)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2022, September). A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. Presented at Parallel Problem Solving from Nature – PPSN

We propose a new approach to generating synthetic instances in the knapsack domain in order to fill an instance-space. The method uses a novelty-search algorithm to search for instances that are diverse with respect to a feature-space but also elicit... Read More about A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem.

Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers (2022)
Presentation / Conference Contribution
Cardoso, R. P., Hart, E., Burth Kurka, D., & Pitt, J. (2022, April). Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers. Presented at EvoSTAR, Madrid

Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient descent to train evolved architectures during the search can be comput... Read More about Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers.

Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn (2022)
Book Chapter
Hart, E. (2022). Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Springer. https://doi.org/1

Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain of interest. Once deployed, the algorithm remains static, failing to impro... Read More about Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn.

Morpho-evolution with learning using a controller archive as an inheritance mechanism (2022)
Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., Winfield, A. F., Hale, M. F., Woolley, R., Angus, M., Timmis, J., & Tyrrell, A. M. (2023). Morpho-evolution with learning using a controller archive as an inheritance mechanism. I

Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller and body-plan could open up many interesting possibilities. However... Read More about Morpho-evolution with learning using a controller archive as an inheritance mechanism.

Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning (2021)
Journal Article
Hart, E., & Le Goff, L. K. (2022). Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning. Philosophical Transactions B: Biological Sciences, 377(1843), https://doi.org/10.1098/rstb.2021.01

We survey and reflect on evolutionary approaches to the joint optimisation of the body and control of a robot, in scenarios where a the goal is to find a design that maximises performance on a specified task. The review is grounded in a general frame... Read More about Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning.

Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models (2021)
Journal Article
Pomponi, F., Luque Anguita, M., Lange, M., D'Amico, B., & Hart, E. (2021). Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models. Frontiers in Built Environment, 7, Article 745598

The construction and operation of buildings account for significant environmental impacts, including greenhouse gas (GHG) emissions, energy demand, resource consumption and waste generation. While the operation of buildings is fairly well regulated a... Read More about Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models.

A Neural Approach to Generation of Constructive Heuristics (2021)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2021, June). A Neural Approach to Generation of Constructive Heuristics. Presented at IEEE Congress on Evolutionary Computation 2021, Kraków, Poland (online)

Both algorithm-selection methods and hyper-heuristic methods rely on a pool of complementary heuristics. Improving the pool with new heuristics can improve performance, however, designing new heuristics can be challenging. Methods such as genetic pro... Read More about A Neural Approach to Generation of Constructive Heuristics.

A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics (2021)
Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021). A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the domain-barrier and are manipulated by the hyper-heuristic itself. However, for... Read More about A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics.

On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme (2021)
Presentation / Conference Contribution
Goff, L. K. L., & Hart, E. (2021, July). On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. Presented at GECCO '21: Genetic and Evolutionary Computation Conference, Lille, France

We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plans while a separate learning algorithm is applied to each body generated to... Read More about On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme.

Using novelty search to explicitly create diversity in ensembles of classifiers (2021)
Presentation / Conference Contribution
Cardoso, R. P., Hart, E., Kurka, D. B., & Pitt, J. V. (2021). Using novelty search to explicitly create diversity in ensembles of classifiers. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference (849-857). https://doi.org/10.

The diversity between individual learners in an ensemble is known to influence its performance. However, there is no standard agreement on how diversity should be defined, and thus how to exploit it to construct a high-performing classifier. We propo... Read More about Using novelty search to explicitly create diversity in ensembles of classifiers.

Automated, Explainable Rule Extraction from MAP-Elites archives (2021)
Presentation / Conference Contribution
Urquhart, N., Höhl, S., & Hart, E. (2021, April). Automated, Explainable Rule Extraction from MAP-Elites archives. Presented at EvoAPPs2021, Online

Quality-diversity(QD) algorithms that return a large archive of elite solutions to a problem provide insights into how high-performing solutions are distributed throughout a feature-space defined by a user — they are often described as illuminating t... Read More about Automated, Explainable Rule Extraction from MAP-Elites archives.

WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets (2021)
Presentation / Conference Contribution
Pitt, J., Burth Kurka, D., Hart, E., & Cardoso, R. P. (2021, April). WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets. Presented at 24th European Conference, EvoApplications 2021, Online

In order to address scalability issues, which can be a challenge for Deep Learning methods, we propose Wide Learning of Diverse Architectures-a model that scales horizontally rather than vertically, enabling distributed learning. We propose a distrib... Read More about WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets.

Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training (2020)
Presentation / Conference Contribution
Panagiaris, N., Hart, E., & Gkatzia, D. (2020, December). Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training. Presented at International Conference on Natural Language Generation (INLG 2020), Dubl

In this paper we consider the problem of optimizing neural Referring Expression Generation (REG) models with sequence level objectives. Recently reinforcement learning (RL) techniques have been adopted to train deep end-to-end systems to directly opt... Read More about Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training.

Evolution of Diverse, Manufacturable Robot Body Plans (2020)
Presentation / Conference Contribution
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., Hale, M. F., Angus, M., Woolley, R., Winfield, A. F., Timmis, J., & Tyrrell, A. M. (2020, December). Evolution of Diverse, Manufacturable Robot Body Plans. Presented at International

Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robots can evolve in real-time and real-space. However, this also introduces new... Read More about Evolution of Diverse, Manufacturable Robot Body Plans.

Hardware Design for Autonomous Robot Evolution (2020)
Presentation / Conference Contribution
Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., De Carlo, M., Timmis, J., Winfield, A. F., Hart, E., Eiben, A. E., & Tyrrell, A. M. (2020, December). Hardware Design for Autonomous Robot Evolution. Presented at International Con

The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The transition for evolutionary designs from purely simulation environments into... Read More about Hardware Design for Autonomous Robot Evolution.

Generating Unambiguous and Diverse Referring Expressions   (2020)
Journal Article
Panagiaris, N., Hart, E., & Gkatzia, D. (2021). Generating Unambiguous and Diverse Referring Expressions  . Computer Speech and Language, 68, Article 101184. https://doi.org/10.1016/j.csl.2020.101184

Neural Referring Expression Generation (REG) models have shown promising results in generating expressions which uniquely describe visual objects. However, current REG models still lack the ability to produce diverse and unambiguous referring express... Read More about Generating Unambiguous and Diverse Referring Expressions  .

Towards Autonomous Robot Evolution (2020)
Book Chapter
Eiben, A. E., Hart, E., Timmis, J., Tyrrell, A. M., & Winfield, A. F. (2021). Towards Autonomous Robot Evolution. In A. Cavalcanti, B. Dongol, R. Hierons, J. Timmis, & J. Woodcock (Eds.), Software Engineering for Robotics (29-51). Springer. https://doi.or

We outline a perspective on the future of evolutionary robotics and discuss a long-term vision regarding robots that evolve in the real world. We argue that such systems offer significant potential for advancing both science and engineering. For scie... Read More about Towards Autonomous Robot Evolution.

Bootstrapping artificial evolution to design robots for autonomous fabrication (2020)
Journal Article
Buchanan, E., Le Goff, L. K., Li, W., Hart, E., Eiben, A. E., De Carlo, M., …Tyrrell, A. M. (2020). Bootstrapping artificial evolution to design robots for autonomous fabrication. Robotics, 9(4), Article 106. https://doi.org/10.3390/robotics9040106

A long-term vision of evolutionary robotics is a technology enabling the evolution of entire autonomous robotic ecosystems that live and work for long periods in challenging and dynamic environments without the need for direct human oversight. Evolut... Read More about Bootstrapping artificial evolution to design robots for autonomous fabrication.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glas

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

On Pros and Cons of Evolving Topologies with Novelty Search (2020)
Presentation / Conference Contribution
Le Goff, L. K., Hart, E., Coninx, A., & Doncieux, S. (2020). On Pros and Cons of Evolving Topologies with Novelty Search. In ALIFE 2020: The 2020 Conference on Artificial Life (423-431). https://doi.org/10.1162/isal_a_00291

Novelty search was proposed as a means of circumventing deception and providing selective pressure towards novel behaviours to provide a path towards open-ended evolution. Initial implementations relied on neuro-evolution approaches which increased n... Read More about On Pros and Cons of Evolving Topologies with Novelty Search.

Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation (2020)
Presentation / Conference Contribution
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., Hale, M. F., Angus, M., Woolley, R., Timmis, J., Winfield, A., & Tyrrell, A. M. (2020, July). Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. Pres

In evolutionary robot systems where morphologies and controllers of real robots are simultaneously evolved, it is clear that there is likely to be requirements to refine the inherited controller of a 'newborn' robot in order to better align it to its... Read More about Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation.

A Deep Learning Approach to Predicting Solutions in Streaming Optimisation Domains (2020)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2020, July). A Deep Learning Approach to Predicting Solutions in Streaming Optimisation Domains. Presented at GECCO ’20, Cancún, Mexico

In the field of combinatorial optimisation, per-instance algorithm selection still remains a challenging problem, particularly with respect to streaming problems such as packing or scheduling. Typical approaches involve training a model to predict th... Read More about A Deep Learning Approach to Predicting Solutions in Streaming Optimisation Domains.

From disorganized equality to efficient hierarchy: how group size drives the evolution of hierarchy in human societies (2020)
Journal Article
Perret, C., Hart, E., & Powers, S. T. (2020). From disorganized equality to efficient hierarchy: how group size drives the evolution of hierarchy in human societies. Proceedings of the Royal Society B: Biological Sciences, 287(1928), Article 20200693. htt

A manifest trend is that larger and more productive human groups shift from distributed to centralized decision-making. Voluntary theories propose that human groups shift to hierarchy to limit scalar stress, i.e. the increase in cost of organization... Read More about From disorganized equality to efficient hierarchy: how group size drives the evolution of hierarchy in human societies.

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites (2020)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2020, April). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. Presented at EvoStar 2020, Seville, Spain

In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi... Read More about Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.

Using MAP-Elites to support policy making around Workforce Scheduling and Routing (2020)
Journal Article
Urquhart, N., Hart, E., & Hutcheson, W. (2020). Using MAP-Elites to support policy making around Workforce Scheduling and Routing. Automatisierungstechnik, 68(2), https://doi.org/10.1515/auto-2019-0107

English abstract: Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be use... Read More about Using MAP-Elites to support policy making around Workforce Scheduling and Routing.

A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution (2019)
Journal Article
Segredo, E., Lalla-Ruiz, E., Hart, E., & Voß, S. (2020). A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution. Computers and Operations Research, 117, Article 104871. https://doi.org/10.10

The success of search-based optimisation algorithms depends on appropriately balancing exploration and exploitation mechanisms during the course of the search. We introduce a mechanism that can be used with Differential Evolution (de) algorithms to a... Read More about A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution.

Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme (2019)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2019). Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme. In Dependability in Sensor, Cloud, and Big Data Systems and Applications (369-382). https://doi.org/10.1007/978-981-15-1

The ability to detect metamorphic malware has generated significant research interest over recent years, particularly given its proliferation on mobile devices. Such malware is particularly hard to detect via signature-based intrusion detection syste... Read More about Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme.

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World (2019)
Presentation / Conference Contribution
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., Angus, M., Veenstra, F., Li, W., Woolley, R., De Carlo, M., & Tyrrell, A. M. (2019, July). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real Worl

The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the major challenges for such a vision is the need to construct many unique ind... Read More about The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World.

Being a leader or being the leader: The evolution of institutionalised hierarchy (2019)
Presentation / Conference Contribution
Perret, C., Hart, E., & Powers, S. T. (2019, July). Being a leader or being the leader: The evolution of institutionalised hierarchy. Presented at ALIFE 2019, Newcastle upon Tyne

Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their personal characteristics, and secondly, as an institutional hierarchy where l... Read More about Being a leader or being the leader: The evolution of institutionalised hierarchy.

Algorithm selection using deep learning without feature extraction (2019)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2019). Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (198-206). https://doi.org/10.1145/3321707.3321845

We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In contrast to the majority of work in algorithm-selection, the approach does... Read More about Algorithm selection using deep learning without feature extraction.

Comparing encodings for performance and phenotypic exploration in evolving modular robots (2019)
Presentation / Conference Contribution
Veenstra, F., Hart, E., Buchanan, E., Li, W., De Carlo, M., & Eiben, A. E. (2019). Comparing encodings for performance and phenotypic exploration in evolving modular robots. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference

To investigate how encodings influence evolving the morphology and control of modular robots, we compared three encodings: a direct encoding and two generative encodings---a compositional pattern producing network (CPPN) and a Lindenmayer System (L-S... Read More about Comparing encodings for performance and phenotypic exploration in evolving modular robots.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Evolving robust policies for community energy system management (2019)
Presentation / Conference Contribution
Cardoso, R., Hart, E., & Pitt, J. (2019, July). Evolving robust policies for community energy system management. Presented at GECCO '19, Prague, Czech Republic

Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each participating community decides whether to self-supply, store, trade, or sel... Read More about Evolving robust policies for community energy system management.

Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. (2019)
Presentation / Conference Contribution
Urquhart, N., Hart, E., & Hutcheson, W. (2019, April). Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. Presented at EvoStar2019: International Conference on the Applications of Evoluti

Quality-diversity algorithms such as MAP-Elites provide a means of supporting the users when finding and choosing solutions to a problem by returning a set of solutions which are diverse according to set of user-defined features. The number of soluti... Read More about Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem..

Use of machine learning techniques to model wind damage to forests (2018)
Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019). Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022

This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms. Models based on these techniques were developed i... Read More about Use of machine learning techniques to model wind damage to forests.

Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments (2018)
Presentation / Conference Contribution
Cardoso, R. P., Rossetti, R. J. F., Hart, E., Kurka, D. B., & Pitt, J. (2018). Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments. In T. Margaria, & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verifica

Electronic institutions are socially-inspired multi-agent systems, typically operating under a set of policies, which are required to determine system operation and to deal with violations and other non-compliant behaviour. They are often faced with... Read More about Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments.

Selection methods and diversity preservation in many-objective evolutionary algorithms (2018)
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018). Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009

Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two main tasks simultaneously. First, it has to promote convergence by selecti... Read More about Selection methods and diversity preservation in many-objective evolutionary algorithms.

On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–1

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains, there is a lack of available heuristics, while for novel problems, no heur... Read More about On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains.

Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites (2018)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2018, September). Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites. Presented at Parallel Problem Solving from Nature (PPSN) 2018, Coimbra, Portugal

Workforce Scheduling and Routing Problems (WSRP) are very common in many practical domains, and usually have a number of objectives. Illumination algorithms such as Map-Elites (ME) have recently gained traction in application to design problems, in p... Read More about Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites.

Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism (2018)
Presentation / Conference Contribution
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018, July). Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. Presented at The 2018 Conference on Artificial Life, Tokyo, Japan

Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders' decisions by aggregating their own and their neighbours' experience, and i... Read More about Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism.

A new rich vehicle routing problem model and benchmark resource (2018)
Presentation / Conference Contribution
Sim, K., Hart, E., Urquhart, N. B., & Pigden, T. (2015, September). A new rich vehicle routing problem model and benchmark resource. Presented at International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with

We describe a new rich VRP model that captures many real-world constraints, following a recently proposed taxonomy that addresses both scenario and problem physical characteristics. The model is used to generate 4800 new instances of rich VRPs which... Read More about A new rich vehicle routing problem model and benchmark resource.

Creating optimised employee travel plans (2018)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2015, September). Creating optimised employee travel plans. Presented at EuroGen 2015

The routing of employees who provide services such as home health or social care is a complex problem. When sending an employee between two addresses , there may exist more than one travel option, e.g. public transport or car. In this paper we examin... Read More about Creating optimised employee travel plans.

A novel similarity-based mutant vector generation strategy for differential evolution (2018)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018, July). A novel similarity-based mutant vector generation strategy for differential evolution. Presented at The Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Kyoto, Japan

The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the search space. However, it is also responsible for promoting intensificatio... Read More about A novel similarity-based mutant vector generation strategy for differential evolution.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Presentation / Conference Contribution
Hart, E., Steyven, A. S. W., & Paechter, B. (2018, July). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. Presented at GECCO 2018, Kyoto, Japan

The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad range of studies that includes insect groups, human groups and swarm robot... Read More about Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm.

Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation (578-593)

In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heuristics often suffice in this case. However, for many domains, a simple heurist... Read More about Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs.

On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems (2018)
Journal Article
Voß, S., Segredo, E., Lalla-Ruiz, E., Hart, E., & Voss, S. (2018). On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems. Expert Systems with Applications, 102

Migrating Birds Optimisation (mbo) is a nature-inspired approach which has been shown to be very effective when solving a variety of combinatorial optimisation problems. More recently, an adaptation of the algorithm has been proposed that enables it... Read More about On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems.

For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems (2017)
Presentation / Conference Contribution
Pitt, J., & Hart, E. (2017). For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W),. https:

This position paper is concerned with the challenge of engineering multi-scale and long-lasting systems, whose operation is regulated by sets of mutually-agreed, conventional rules. The core of the problem is that there are multiple, inter-dependent... Read More about For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems.

Emergence of hierarchy from the evolution of individual influence in an agent-based model (2017)
Presentation / Conference Contribution
Perret, C., Powers, S. T., & Hart, E. (2017). Emergence of hierarchy from the evolution of individual influence in an agent-based model. In Proceedings of the 14th European Conference on Artificial Life 2017 (348-355)

The sudden transition from egalitarian groups to hierarchical societies that occurred with the origin of agriculture is one of the most striking features of the evolution of human societies. Hierarchy is reflected by the evolution of an asymmetrical... Read More about Emergence of hierarchy from the evolution of individual influence in an agent-based model.

Impact of selection methods on the diversity of many-objective Pareto set approximations (2017)
Presentation / Conference Contribution
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017, September). Impact of selection methods on the diversity of many-objective Pareto set approximations. Presented at 21st International Conference on Knowledge-Based and Intelligent Information & E

Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultaneously. First of all, they must select individuals that are as close as poss... Read More about Impact of selection methods on the diversity of many-objective Pareto set approximations.

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector (2017)
Presentation / Conference Contribution
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017). A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (1121

Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing risk assessment methods is thus one of the keys to finding forest management... Read More about A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector.

On Constructing Ensembles for Combinatorial Optimisation (2017)
Journal Article
Hart, E., & Sim, K. (2018). On Constructing Ensembles for Combinatorial Optimisation. Evolutionary Computation, 26(1), 67-87. https://doi.org/10.1162/evco_a_00203

Although the use of ensemble methods in machine-learning is ubiquitous due to their proven ability to outperform their constituent algorithms, ensembles of optimisation algorithms have received relatively little attention. Existing approaches lag beh... Read More about On Constructing Ensembles for Combinatorial Optimisation.

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics (2017)
Presentation / Conference Contribution
Steyven, A., Hart, E., & Paechter, B. (2017). An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (155-162).

A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. However, the role played by the environment in influencing the effectiveness o... Read More about An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics.

Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation (2016)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016, May). Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. Presented at Learning and Intelligent OptimizatioN Conference LION 10, Ischi

Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic which can apply one of two meta-heuristics at the current stage of the search.... Read More about Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation.

Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems (2016)
Presentation / Conference Contribution
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016). Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (C

In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control scheme based on both Fuzzy Logic Controllers (FLCs) and Hyper-heuristics (HHs).... Read More about Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems.

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems (2016)
Presentation / Conference Contribution
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016, September). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. Presented at 14th International Conference on Parallel Problem Sol

We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), t... Read More about Analysing the performance of migrating birds optimisation approaches for large scale continuous problems.

Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm (2016)
Presentation / Conference Contribution
Steyven, A., Hart, E., & Paechter, B. (2016, October). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. Presented at PPSN 2016 14th International Conference on Parallel Problem Solving from Nature

It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear exactly how parameterisation of a given environment might influence the emer... Read More about Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm.

Artificial Immunology for Collective Adaptive Systems Design and Implementation (2016)
Journal Article
Capodieci, N., Hart, E., & Cabri, G. (2016). Artificial Immunology for Collective Adaptive Systems Design and Implementation. ACM transactions on autonomous and adaptive systems, 11(2), 1-25. https://doi.org/10.1145/2897372

Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms to deal with an unpredictable and changing environment. Existing frameworks for engin... Read More about Artificial Immunology for Collective Adaptive Systems Design and Implementation.

A hyper-heuristic ensemble method for static job-shop scheduling. (2016)
Journal Article
Hart, E., & Sim, K. (2016). A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance... Read More about A hyper-heuristic ensemble method for static job-shop scheduling..

A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules (2015)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2015). A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules. In GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

A previously described hyper-heuristic framework named NELLI is adapted for the classic Job Shop Scheduling Problem (JSSP) and used to find ensembles of reusable heuristics that cooperate to cover the heuristic search space. A new heuristic generato... Read More about A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules.

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. (2015)
Presentation / Conference Contribution
Hart, E., Steyven, A., & Paechter, B. (2015). Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. In Proceedings of the 2015 on Genetic and Evolution

Ensuring the integrity of a robot swarm in terms of maintaining a stable population of functioning robots over long periods of time is a mandatory prerequisite for building more complex systems that achieve user-defined tasks. mEDEA is an environ... Read More about Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication..

Grid diversity operator for some population-based optimization algorithms. (2015)
Presentation / Conference Contribution
Salah, A., & Hart, E. (2015). Grid diversity operator for some population-based optimization algorithms. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15 (1475-1476). https:/

We present a novel diversity method named Grid Diversity Operator (GDO) that can be incorporated into multiple population-based optimization algorithms that guides the containing algorithm in creating new individuals in sparsely visited areas of... Read More about Grid diversity operator for some population-based optimization algorithms..

Multi-Modal employee routing with time windows in an urban environment. (2015)
Presentation / Conference Contribution
Urquhart, N. B., Hart, E., & Judson, A. (2015, July). Multi-Modal employee routing with time windows in an urban environment

An urban environment provides a number of challenges and opportunities for organisations faced with the task of scheduling a mobile workforce. Given a mixed set of public and private transportation and a list of scheduling constraints, we seek to... Read More about Multi-Modal employee routing with time windows in an urban environment..

Roll Project Job Shop scheduling benchmark problems. (2015)
Data
Hart, E., & Sim, K. (2015). Roll Project Job Shop scheduling benchmark problems. [Dataset]. https://doi.org/10.17869/ENU.2015.9365

This document describes two sets of benchmark problem instances for the job shop scheduling problem. Each set of instances is supplied as a compressed (zipped) archive containing a single CSV file for each problem instance using the format described... Read More about Roll Project Job Shop scheduling benchmark problems..

Roll Project Rich Vehicle Routing benchmark problems. (2015)
Data
Hart, E., & Sim, K. (2015). Roll Project Rich Vehicle Routing benchmark problems. [Data]. https://doi.org/10.17869/ENU.2015.9367

This document describes a large set of Benchmark Problem Instances for the Rich Vehicle Routing Problem. All files are supplied as a single compressed (zipped) archive containing the instances, in XML format, an Object-Oriented Model supplied in XSD... Read More about Roll Project Rich Vehicle Routing benchmark problems..

Creating optimised employee travel plans. (2015)
Presentation / Conference Contribution
Urquhart, N. B., & Hart, E. (2015, September). Creating optimised employee travel plans. Paper presented at International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societa

The Cost of Communication: Environmental Pressure and Survivability in mEDEA (2015)
Presentation / Conference Contribution
Steyven, A., Hart, E., & Paechter, B. (2015, July). The Cost of Communication: Environmental Pressure and Survivability in mEDEA. Presented at GECCO ’15

We augment the mEDEA algorithm to explicitly account for the costs of communication between robots. Experimental results show that adding a costs for communication exerts environmental pressure to implicitly select for genomes that maintain high... Read More about The Cost of Communication: Environmental Pressure and Survivability in mEDEA.

A research agenda for metaheuristic standardization. (2015)
Presentation / Conference Contribution
Hart, E., & Sim, K. (2015, June). A research agenda for metaheuristic standardization. Paper presented at 11th Metaheuristics International Conference

We propose that the development of standardized, explicit, machine-readable descriptions of metaheuris- tics will greatly advance scientific progress in the field. In particular, we advocate a purely functional description of metaheuristics — separat... Read More about A research agenda for metaheuristic standardization..

Collaborative Diffusion on the GPU for Path-Finding in Games (2015)
Presentation / Conference Contribution
McMillan, C., Hart, E., & Chalmers, K. (2015). Collaborative Diffusion on the GPU for Path-Finding in Games. In A. M. Mora, & G. Squillero (Eds.), Applications of Evolutionary Computation; Lecture Notes in Computer Science (418-429). https://doi.org/10.10

Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical game environments. We describe a parallel implementation of a collaborative d... Read More about Collaborative Diffusion on the GPU for Path-Finding in Games.

A Lifelong Learning Hyper-heuristic Method for Bin Packing (2015)
Journal Article
Hart, E., Sim, K., & Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121

We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; representative problems and heur... Read More about A Lifelong Learning Hyper-heuristic Method for Bin Packing.

Artificial Immune System driven evolution in Swarm Chemistry. (2014)
Presentation / Conference Contribution
Capodieci, N., Hart, E., & Cabri, G. (2014). Artificial Immune System driven evolution in Swarm Chemistry. In Proceedings of IEEE SASO 2014 (40-49). https://doi.org/10.1109/SASO.2014.16

Morphogenetic engineering represents an interesting field in which models, frameworks and algorithms can be tested in order to study how self-* properties and emergent behaviours can arise in potentially complex and distributed systems. In this field... Read More about Artificial Immune System driven evolution in Swarm Chemistry..

Idiotypic networks for evolutionary controllers in virtual creatures. (2014)
Presentation / Conference Contribution
Capodieci, N., Hart, E., & Cabri, G. (2014). Idiotypic networks for evolutionary controllers in virtual creatures. In H. Sayama, J. Rieffel, S. Risi, R. Doursat, & H. Lipson (Eds.), Artificial Life 14: Proceedings of ALife, 14th International Conference o

We propose a novel method for evolving adaptive locomotive strategies for virtual limbless creatures that addresses both functional and non-functional requirements, respectively the ability to avoid obstacles and to minimise spent energy. We describe... Read More about Idiotypic networks for evolutionary controllers in virtual creatures..

On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system. (2014)
Presentation / Conference Contribution
Hart, E., & Sim, K. (2014). On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system. In Proceedings of PPSN, 13th International Conference on Parallel problem Solving from Nature (282-291). https://doi.org/10.1007/978-3-

Real-world applications of optimisation techniques place more importance on finding approaches that result in acceptable quality solutions in a short time-frame and can provide robust solutions, capable of being modified in response to changes in the... Read More about On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system..

A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation (2014)
Journal Article
Segredo, E., Segura, C., León, C., & Hart, E. (2015). A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-14

In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The ability to deal with premature convergence has been greatly improved with... Read More about A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation.

A real-world employee scheduling and routing application. (2014)
Presentation / Conference Contribution
Hart, E., Sim, K., & Urquhart, N. B. (2014). A real-world employee scheduling and routing application. In C. Igel (Ed.), GECCO 2014 Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation (1239-1242).

We describe a hyper-heuristic application developed for a client to find quick, acceptable solutions to Workforce Schedul- ing and Routing problems. An interactive fitness function controlled by the user enables five different objectives to be weight... Read More about A real-world employee scheduling and routing application..

An improved immune inspired hyper-heuristic for combinatorial optimisation problems. (2014)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2014). An improved immune inspired hyper-heuristic for combinatorial optimisation problems. In C. Igel (Ed.), Proceedings of GECCO 2014 (Genetic and Evolutionary Computation Conference) (121-128). https://doi.org/10.1145/2576768.25982

The meta-dynamics of an immune-inspired optimisation sys- tem NELLI are considered. NELLI has previously shown to exhibit good performance when applied to a large set of optimisation problems by sustaining a network of novel heuristics. We address th... Read More about An improved immune inspired hyper-heuristic for combinatorial optimisation problems..

General and craniofacial development are complex adaptive processes influenced by diversity (2014)
Journal Article
Hart, E., Brook, A. H., Brook-O'Donnell, M., Hone, A., Hughes, T., & Smith, R. (2014). General and craniofacial development are complex adaptive processes influenced by diversity. Australian Dental Journal, 59(S1), 13-22. https://doi.org/10.1111/adj.12158

Complex systems are present in such diverse areas as social systems, economies, ecosystems and Biology and, therefore, are highly relevant to dental research, education and practice. A Complex Adaptive System in biological development is a dynamic pr... Read More about General and craniofacial development are complex adaptive processes influenced by diversity.

Designing self-aware adaptive systems: from autonomic computing to cognitive immune networks. (2013)
Presentation / Conference Contribution
Capodieci, N., Hart, E., & Cabri, G. (2013). Designing self-aware adaptive systems: from autonomic computing to cognitive immune networks. In Proceedings of SASO Workshops 2013. https://doi.org/10.1109/SASOW.2013.17

An autonomic system is composed of ensembles of heterogeneous autonomic components in which large sets of components are dynamically added and removed. Nodes within such an ensemble should cooperate to achieve system or human goals, and systems are e... Read More about Designing self-aware adaptive systems: from autonomic computing to cognitive immune networks..

An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics. (2013)
Presentation / Conference Contribution
Capodieci, N., Hart, E., & Cabri, G. (2013). An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artifical Life, Proc

We describe an immune inspired approach to achieve self-expression within an ensemble, i.e. enabling an ensemble of autonomic components to dynamically change their coordination pattern during the runtime execution of a given task. Building on previo... Read More about An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics..

On the role of the AIS practitioner. (2013)
Presentation / Conference Contribution
Hart, E., Read, M., McEwan, C., Aickelin, U., & Greensmith, J. (2013). On the role of the AIS practitioner. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL 2013 (891-892). https://doi.org/10.7551/978-0-2

Cognisant of the gulf between engineers and immunologists that currenty hinders a truly inter-disciplinary approach to the field of Artificial Immune Systems (AIS), we propose a redefinition of the term AIS practitioner, as an individual who iden... Read More about On the role of the AIS practitioner..

Learning to solve bin packing problems with an immune inspired hyper-heuristic. (2013)
Presentation / Conference Contribution
Sim, K., Hart, E., & Paechter, B. (2013). Learning to solve bin packing problems with an immune inspired hyper-heuristic. In P. Liò, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL 2013 (856-863). https://doi.org/1

Motivated by the natural immune system's ability to defend the body by generating and maintaining a repertoire of antibodies that collectively cover the potential pathogen space, we describe an artificial system that discovers and maintains a reperto... Read More about Learning to solve bin packing problems with an immune inspired hyper-heuristic..

Incorporating emissions models within a multi-objective vehicle routing problem. (2013)
Presentation / Conference Contribution
Urquhart, N. B., Scott, C., & Hart, E. (2013, July). Incorporating emissions models within a multi-objective vehicle routing problem. Presented at 15th annual conference companion on Genetic and evolutionary computation

The vehicle routing problem with time windows (VRPTW) has previously been investigated as a multi-objective problem. In this paper estimated carbon emissions is added as an objective alongside the number of vehicles required and distance travelled. W... Read More about Incorporating emissions models within a multi-objective vehicle routing problem..

Generating single and multiple cooperative heuristics for the one dimensional bin packing problem using a single node genetic programming island model. (2013)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2013). Generating single and multiple cooperative heuristics for the one dimensional bin packing problem using a single node genetic programming island model. In E. Alba (Ed.), Proceedgs of GECCO 2013 (1549-1556). https://doi.org/10.1

Novel deterministic heuristics are generated using Single Node Genetic Programming for application to the One Dimensional Bin Packing Problem. First a single deterministic heuristic was evolved that minimised the total number of bins used when applie... Read More about Generating single and multiple cooperative heuristics for the one dimensional bin packing problem using a single node genetic programming island model..

Using graphical information systems to improve vehicle routing problem instances. (2013)
Presentation / Conference Contribution
Urquhart, N. B., Scott, C., & Hart, E. (2013, July). Using graphical information systems to improve vehicle routing problem instances. Presented at 15th annual conference companion on Genetic and evolutionary computation

This paper makes the assertion that vehicle routing rearch has produced increasingly more powerful problem solvers, but has not increased the realism or compexity of typical problem instances. This paper argues that the time has come of use realistic... Read More about Using graphical information systems to improve vehicle routing problem instances..

A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution. (2012)
Presentation / Conference Contribution
Sim, K., Hart, E., & Paechter, B. (2012). A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution. In Parallel Problem Solving from Nature: PPSN XII (348-357). https://doi.org/10.100

A hyper-heuristic for the one dimensional bin packing problem is presented that uses an Evolutionary Algorithm (EA) to evolve a set of attributes that characterise a problem instance. The EA evolves divisions of variable quantity and dimension that r... Read More about A Hyper-Heuristic classifier for one dimensional bin packing problems: Improving classification accuracy by attribute evolution..

This pervasive day: creative Interactive methods for encouraging public engagement with FET research (2011)
Journal Article
Helgason, I., Bradley, J., Egan, C., Paechter, B., & Hart, E. (2011). This pervasive day: creative Interactive methods for encouraging public engagement with FET research. Procedia Computer Science, 7, 207-208. https://doi.org/10.1016/j.procs.2011.09.028

This paper describes a case study of a programme of interactive public engagement activities presented by the PerAda Co-ordination Action project (FET Proactive Initiative on Pervasive Adaptation) [1] in 2011. The intention behind these events was to... Read More about This pervasive day: creative Interactive methods for encouraging public engagement with FET research.

An engineering-Informed modelling approach to AIS. (2011)
Presentation / Conference Contribution
Hart, E., & Davoudani, D. (2011). An engineering-Informed modelling approach to AIS. In Proceedings of International Conference on Artificial Immune Systems (ICARIS 2010) (240-253). https://doi.org/10.1007/978-3-642-22371-6_22

A recent shift in thinking in Artificial Immune Systems (AIS) advocates developing a greater understanding of the underlying biological systems that serve as inspiration for engineering such systems by developing abstract computational models of t... Read More about An engineering-Informed modelling approach to AIS..

Advances in artificial immune systems (2011)
Journal Article
Hart, E., McEwan, C., Timmis, J., & Hone, A. (2011). Advances in artificial immune systems. Evolutionary Intelligence, 4, 67-68. https://doi.org/10.1007/s12065-011-0058-z

The field of Artificial Immune Systems (AIS) derives inspiration from processes and mechanisms apparent in the biological immune system. After early applications of this paradigm to problems in anomaly detection and classification, the field rapidly... Read More about Advances in artificial immune systems.

Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings (2010)
Presentation / Conference Contribution
(2010). Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems, ICARIS 2010, Proceedings of 9th International Confer

Artificial immune systems (AIS) is a diverse and maturing area of research that bridges the disciplines of immunology and computation. The original research impetus in AIS had a clear focus on applying immunological principles to computational proble... Read More about Artificial Immune Systems: 9th International Conference, ICARIS 2010, Edinburgh, UK, July 26-29, 2010, Proceedings.

Towards self-aware PerAda systems. (2010)
Presentation / Conference Contribution
Hart, E., & Paechter, B. (2010). Towards self-aware PerAda systems. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010 Proceedings (314-216). https://doi.org/10.1007/978-3-642-14547-6_2

Pervasive Adaptation (PerAda) refers to massive-scale pervasive information and communication systems which are capable of autonomously adapting to highly dynamic and open technological and user contexts. PerAda systems are thus a special case of col... Read More about Towards self-aware PerAda systems..

Clonal selection from first principles. (2010)
Presentation / Conference Contribution
McEwan, C., & Hart, E. (2010). Clonal selection from first principles. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems, Proceedings of 9th International Conference, ICARIS 2010 (18-32). https://doi.org/10.1007/978-3-642-14547

Clonal selection is the keystone of mainstream immunology and computational systems based on immunological principles. For the latter, clonal selection is often interpreted as an asexual variant of natural selection, and thus, tend to be variation... Read More about Clonal selection from first principles..

Symbiotic cognitive networks: a proposal. (2010)
Presentation / Conference Contribution
Rasheed, T., Hart, E., Falconer, R., & Bown, J. (2010). Symbiotic cognitive networks: a proposal. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010 Proceedings (326-328). https://doi.o

We describe the concept of a cognitive network and propose that ecosystems of co-existing networks which are globally energy efficient while providing the expected quality of service can be realised by exploiting two mechanisms which occur in biologi... Read More about Symbiotic cognitive networks: a proposal..

Influence of topology and payload on CO2 optimised vehicle routing (2010)
Presentation / Conference Contribution
Scott, C., Urquhart, N. B., & Hart, E. (2010). Influence of topology and payload on CO2 optimised vehicle routing. In Applications of Evolutionary Computing (141-150). https://doi.org/10.1007/978-3-642-12242-2_15

This paper investigates the influence of gradient and payload correction factors used within a CO2 emission model on the solutions to shortest path and travelling salesman problems when applied to freight delivery. Problem instances based on real li... Read More about Influence of topology and payload on CO2 optimised vehicle routing.

Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem (2010)
Presentation / Conference Contribution
Urquhart, N. B., Scott, C., & Hart, E. (2010). Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem. In C. Chio, A. Brabazon, G. A. Di Caro, M. Ebner, M. Farooq, A. Fink, …N. Urquhart (Eds.), Applications of evo

This paper examines the issues surrounding the effects of using vehicle emissions as the fitness criteria when solving routing problems using evolutionary techniques. The case-study examined is that of the Travelling Salesman Problem (TSP) based upon... Read More about Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem.

Building low CO2 solutions to the vehicle routing problem with time windows using an evolutionary algorithm. (2010)
Presentation / Conference Contribution
Urquhart, N. B., Hart, E., & Scott, C. (2010). Building low CO2 solutions to the vehicle routing problem with time windows using an evolutionary algorithm. In IEEE Congress on Evolutionary Computation. https://doi.org/10.1109/CEC.2010.5586088

An evolutionary Multi-Objective Algorithm (MOA) is used to investigate the trade-off between CO2 savings, distance and number of vehicles used in a typical vehicle routing problem with Time Windows (VRPTW). A problem set is derived containing three... Read More about Building low CO2 solutions to the vehicle routing problem with time windows using an evolutionary algorithm..

On artificial immune systems and swarm intelligence (2010)
Journal Article
Timmis, J., Andrews, P., & Hart, E. (2010). On artificial immune systems and swarm intelligence. Swarm Intelligence, 4(4), 247-273. https://doi.org/10.1007/s11721-010-0045-5

This position paper explores the nature and role of two bio-inspired paradigms, namely Artificial Immune Systems (AIS) and Swarm Intelligence (SI). We argue that there are many aspects of AIS that have direct parallels with SI and examine the role of... Read More about On artificial immune systems and swarm intelligence.

New network paradigms (2010)
Book
(2010). E. Altman, T. Basar, E. Hart, D. Miorandi, A. Moustakas, & S. Toumpis (Eds.), New network paradigms. Elsevier

Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems (2009)
Book Chapter
Hart, E., McEwan, C., & Davoudani, D. (2009). Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems. In C. Mumford, & L. Jain (Eds.), Intelligent Systems Reference Library; Computational Intelligence (527-558). Springer-V

Despite a steady increase in the application of algorithms inspired by the natural immune system to a variety of domains over the previous decade, we argue that the field of Artificial Immune Systems has yet to achieve its full potential. We suggest... Read More about Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems.

On AIRS and clonal selection for machine learning (2009)
Presentation / Conference Contribution
McEwan, C., & Hart, E. (2009). On AIRS and clonal selection for machine learning. In Artificial Immune Systems (67-79). https://doi.org/10.1007/978-3-642-03246-2_11

Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex network theory, particularly in the area of small-world and scale-free top... Read More about On AIRS and clonal selection for machine learning.

Dendritic cell trafficking: from Immunology to Engineering. (2009)
Presentation / Conference Contribution
Hart, E., & Davoudani, D. (2009). Dendritic cell trafficking: from Immunology to Engineering. In Artificial Immune Systems (11-13). https://doi.org/10.1007/978-3-642-03246-2_4

The field of Artificial Immune Systems (AIS) has derived inspiration from many different elements of the natural immune system in order to develop engineered systems that operate in environments with constraints similar to those faced by the immune s... Read More about Dendritic cell trafficking: from Immunology to Engineering..

Structure versus function: a topological perspective on immune networks (2009)
Journal Article
Hart, E., Bersini, H., & Santos, F. (2009). Structure versus function: a topological perspective on immune networks. Natural Computing, https://doi.org/10.1007/s11047-009-9138-8

Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex network theory, particularly in the area of small-world and scale-free top... Read More about Structure versus function: a topological perspective on immune networks.

Representation in the (Artificial) Immune System (2009)
Journal Article
McEwan, C., & Hart, E. (2009). Representation in the (Artificial) Immune System. Journal of Mathematical Modelling and Algorithms, 8, 125-149. https://doi.org/10.1007/s10852-009-9104-6

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dich... Read More about Representation in the (Artificial) Immune System.

Computing the State of Specknets: an immune-inspired approach. (2009)
Presentation / Conference Contribution
Davoudani, D., Hart, E., & Paechter, B. (2009). Computing the State of Specknets: an immune-inspired approach. In Performance Evaluation of Computer and Telecommunication Systems, 2008. SPECTS 2008. International Symposium on (52-59)

Speckled Computing is an emerging technology based on the deployment of thousands of minute semiconductor grains in dense, wireless networks known as Specknets. Specknets collect and process data to achieve some application dependent functionalit... Read More about Computing the State of Specknets: an immune-inspired approach..

Computing the State of Specknets: further analysis of an innate immune-inspired model. (2008)
Presentation / Conference Contribution
Davoudani, D., Hart, E., & Paechter, B. (2008). Computing the State of Specknets: further analysis of an innate immune-inspired model. In P. Bentley, D. Lee, & S. Jung (Eds.), Artificial Immune Systems, 7th International Conference, ICARIS 2008, Phuket, T

Specknets consist of hundreds of miniature devices, which are each capable of processing data and communicating wirelessly across short distances. Such networks, with their great complexity, pose considerable challenges for engineers due to the unrel... Read More about Computing the State of Specknets: further analysis of an innate immune-inspired model..

Immuno-engineering (2008)
Presentation / Conference Contribution
Timmis, J., Hart, E., Hone, A., Neal, M., Robins, A., Stepney, S., & Tyrrell, A. (2008). Immuno-engineering. In M. Hinchey, A. Pagnoni, F. J. Rammig, & H. Schmeck (Eds.), Biologically-inspired collaborative computing (3-18). https://doi.org/10.1007/978-0-

In this position paper, we outline a vision for a new type of engineering: immuno-engineering, that can be used for the development of biologically grounded and theoretically understood Artificial Immune Systems (AIS). We argue that, like many bio-in... Read More about Immuno-engineering.

Boosting the Immune System (2008)
Presentation / Conference Contribution
McEwan, C., Hart, E., & Paechter, B. (2008). Boosting the Immune System. In Artificial Immune Systems (316-327). https://doi.org/10.1007/978-3-540-85072-4_28

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or modelling biologically plausible dynamical systems, with little overlap between. Although the balance is la... Read More about Boosting the Immune System.

Application areas of AIS: The past, the present and the future (2008)
Journal Article
Hart, E., & Timmis, J. (2008). Application areas of AIS: The past, the present and the future. Applied Soft Computing, 8(1), 191-201. https://doi.org/10.1016/j.asoc.2006.12.004

After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the paradigm has brought to the application areas to which it has been applied. Undeniably, there have... Read More about Application areas of AIS: The past, the present and the future.

Immunological inspiration for building a new generation of autonomic systems. (2007)
Presentation / Conference Contribution
Hart, E., Davoudani, D., & McEwan, C. (2007). Immunological inspiration for building a new generation of autonomic systems. In Autonomics '07 Proceedings of the 1st international conference on Autonomic computing and communication systems

Autonomic computing systems of the future will be required to exhibit a number of properties which cannot be engineered using current technologies and algorithms. The most direct inspiration for building such systems is nature, where for example the... Read More about Immunological inspiration for building a new generation of autonomic systems..

An Immune-Inspired Approach to Speckled Computing (2007)
Presentation / Conference Contribution
Davoudani, D., Hart, E., & Paechter, B. (2007, August). An Immune-Inspired Approach to Speckled Computing. Presented at International Conference on Artificial Immune Systems ICARIS 2007, Beijing, China

Speckled Computing offers a radically new concept in information technology that has the potential to revolutionise the way we communicate and exchange information. Specks — minute, autonomous, semi-conductor grains that can sense and compute locally... Read More about An Immune-Inspired Approach to Speckled Computing.

Revisiting the Central and Peripheral Immune System (2007)
Presentation / Conference Contribution
McEwan, C., Hart, E., & Paechter, B. (2007, August). Revisiting the Central and Peripheral Immune System. Presented at ICARIS 2007: International Conference on Artificial Immune Systems, Santos, Brazil

The idiotypic network has a long and chequered history in both theoretical immunology and Artificial Immune Systems. In terms of the latter, the drive for engineering applications has led to a diluted interpretation of the immunological models. Resea... Read More about Revisiting the Central and Peripheral Immune System.

Topological constraints in the evolution of idiotypic networks. (2007)
Presentation / Conference Contribution
Hart, E., Santos, F., & Bersini, H. (2007). Topological constraints in the evolution of idiotypic networks. In Artificial Immune Systems: Proceedings of 6th International Conference, ICARIS 2007 (252-263). https://doi.org/10.1007/978-3-540-73922-7_22

Previous studies have shown that there is an intricate relationship between the topology of an idiotypic network and its resulting properties. However, empirical studies can only be performed by pre-selecting both a shape-space and affinity function.... Read More about Topological constraints in the evolution of idiotypic networks..

How affinity influences tolerance in an idiotypic network. (2007)
Journal Article
Hart, E., Bersini, H., & Santos, F. (2007). How affinity influences tolerance in an idiotypic network. Journal of Theoretical Biology, 249, 422-436. https://doi.org/10.1016/j.jtbi.2007.07.019

The mutability of bacteriophages offers a particular advantage in the treatment of bacterial infections not afforded by other antimicrobial therapies. When phage-resistant bacteria emerge, mutation may generate phage capable of exploiting and thus li... Read More about How affinity influences tolerance in an idiotypic network..

An overview of artificial immune systems. (2005)
Book Chapter
Timmis, J., Knight, T., de Castro, L., & Hart, E. (2005). An overview of artificial immune systems. In R. Paton, H. Bolouri, W. M. L. Holcombe, J. H. Parish, & R. Tateson (Eds.), Computation in Cells and Tissues: Perspectives and Tools of Thought (51-86).

The immune system is highly distributed, highly adaptive, self-organising in nature, maintains a memory of past encounters and has the ability to continually learn about new encounters. From a computational point of view, the immune system has much t... Read More about An overview of artificial immune systems..

Evolutionary scheduling: a review. (2005)
Journal Article
Hart, E., Ross, P., & Corne, D. (2005). Evolutionary scheduling: a review. Genetic Programming and Evolvable Machines, 6, 191-220. https://doi.org/10.1007/s10710-005-7580-7

Early and seminal work which applied evolutionary computing methods to scheduling problems from 1985 onwards laid a strong and exciting foundation for the work which has been reported over the past decade or so. A survey of the current state-of-the-a... Read More about Evolutionary scheduling: a review..

The impact of the shape of antibody recognition regions on the emergence of idiotypic networks. (2005)
Journal Article
Hart, E., & Ross, P. (2005). The impact of the shape of antibody recognition regions on the emergence of idiotypic networks. International Journal of Unconventional Computing, 1, 281-313

One of the components of an AIS algorithm that most distinguishes it from other paradigms is the use of an affinity funciton. However, for the most part, the implications of choosing a suitable matching rule and the likely effects on the algorithm fr... Read More about The impact of the shape of antibody recognition regions on the emergence of idiotypic networks..

Evolutionary Computation Combinatorial Optimization. (2004)
Journal Article
(2004). Evolutionary Computation Combinatorial Optimization. Journal of Mathematical Modelling and Algorithms, 3(4),

Guest Editor of Special issue of Journal of Mathematical Modelling and Algorithms

Requirements for getting a robot to grow-up (2003)
Presentation / Conference Contribution
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P., & Morgavi, G. (2003). Requirements for getting a robot to grow-up. In W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, & J. Ziegler (Eds.), Advances in Artificial Life 7th European Conferen

Much of current robot research is about learning tasks in which the task to be achieved is pre-specified, a suitable technology for the task is chosen and the learning process is then experimentally investigated. In this paper we discuss a different... Read More about Requirements for getting a robot to grow-up.

Exploiting the analogy between the immune system and sparse distributed memory. (2003)
Journal Article
Hart, E., & Ross, P. (2003). Exploiting the analogy between the immune system and sparse distributed memory. Genetic Programming and Evolvable Machines, 4(4), 333-358. https://doi.org/10.1023/a%3A1026191011609

The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for clustering non-stationary data based on a combination of salient features... Read More about Exploiting the analogy between the immune system and sparse distributed memory..

Artificial immune systems: proceedings of the 2nd international conference. (2003)
Presentation / Conference Contribution
(2003). Artificial immune systems: proceedings of the 2nd international conference. In J. Timmis, P. J. Bentley, & E. Hart (Eds.), Artificial Immune Systems: Proceedings of the 2nd International Conference,. https://doi.org/10.1007/b12020

This book constitutes the refereed proceedings of the Second International Conference on Artificial Immune Systems, ICARIS 2003, held in Edinburgh, UK in September 2003

Genetic algorithms and timetabling (2003)
Book Chapter
Ross, P., Hart, E., & Corne, D. (2003). Genetic algorithms and timetabling. In A. Ghosh, & K. Tsutsui (Eds.), Advances in Evolutionary Optimisation. Springer. https://doi.org/10.1007/978-3-642-18965-4_30

Genetic algorithms can be used to search very large spaces, and it would seem natural to use them for tackling the nastier kinds of timetabling problem. We completed an EPSRC-funded project on this last year, and distribute a free package that handle... Read More about Genetic algorithms and timetabling.

A role for immunology in 'next generation' robots. (2003)
Presentation / Conference Contribution
Hart, E., Ross, P., Webb, A., & Lawson, A. (2003). A role for immunology in 'next generation' robots. In J. Timmis, P. Bentley, & E. Hart (Eds.), Artificial Immune Systems. ICARIS 2003 (46-56). https://doi.org/10.1007/978-3-540-45192-1_5

Much of current robot research is about learning tasks in which the task to be achieved is pre-specified, a suitable technology for the task is chosen and the learning process is experimentally investigated. A more interesting research question is ho... Read More about A role for immunology in 'next generation' robots..

Controlling a simulated Khepera with an XCS classifier system with memory. (2003)
Presentation / Conference Contribution
Webb, A., Hart, E., Ross, P., & Lawson, A. (2003). Controlling a simulated Khepera with an XCS classifier system with memory.

Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of action. One technique for addressing this problem is to use additional interna... Read More about Controlling a simulated Khepera with an XCS classifier system with memory..

Requirements for getting a robot to grow up. (2003)
Presentation / Conference Contribution
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P., & Morgavi, G. (2003). Requirements for getting a robot to grow up.

Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. (2003)
Presentation / Conference Contribution
Ross, P., Marin-Blazquez, J. G., Schulenburg, S., & Hart, E. (2003). Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics.

The idea underlying hyper-heuristics is to discover some combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be worthwhile, such a combination should outperform all of the constituent heur... Read More about Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics..

A systematic investigation of GA performance on jobshop scheduling problems. (2003)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2003). A systematic investigation of GA performance on jobshop scheduling problems. In Real-World Applications of Evolutionary Computing (280-289). https://doi.org/10.1007/3-540-45561-2_27

Although there has been a wealth of work reported in the literature on the application of genetic algorithms (GAs) to jobshop scheduling problems, much of it contains some gross over-generalisations, i.e that the observed performance of a GA on a sma... Read More about A systematic investigation of GA performance on jobshop scheduling problems..

Exploiting the analogy between immunology and sparse distributed memory. (2002)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2002). Exploiting the analogy between immunology and sparse distributed memory. In J. Timmis, & P. J. Bentley (Eds.), ICARIS 2002 : 1st International Conference on Artificial Immune Systems (59-67)

The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for clustering non-stationary data based on a combination of salient features... Read More about Exploiting the analogy between immunology and sparse distributed memory..

Combining choices of heuristics. (2002)
Book Chapter
Ross, P., & Hart, E. (2002). Combining choices of heuristics. In R. Sarker, M. Mohammadian, & X. Yao (Eds.), Evolutionary Optimization (229-252). Kluwer

Multiple-goal learning in robots using the MAXSON neural network architecture. (2002)
Presentation / Conference Contribution
Webb, A., Ross, P., & Hart, E. (2002). Multiple-goal learning in robots using the MAXSON neural network architecture. In B. Hallam, D. Floreano, G. Hayes, J. A. Meyere, & J. Hallam (Eds.), SAB'02 Workshop: On Growing Up Artifacts that Live - Basic Princip

No abstract available.

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems.

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..

GAVEL - a new tool for genetic algorithm visualization (2001)
Journal Article
Hart, E., & Ross, P. (2001). GAVEL - a new tool for genetic algorithm visualization. IEEE Transactions on Evolutionary Computation, 5(4), 335-348. https://doi.org/10.1109/4235.942528

This paper surveys the state of the art in evolutionary algorithm visualization and describes a new tool called GAVEL. It provides a means to examine in a genetic algorithm (GA) how crossover and mutation operations assembled the final result, where... Read More about GAVEL - a new tool for genetic algorithm visualization.

Clustering Moving Data with a Modified Immune Algorithm (2001)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2001). Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing (394-403). https://doi.org/10.1007/3-540-45365-2_41

In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering have been proposed, none appear to specifically address the task of clustering... Read More about Clustering Moving Data with a Modified Immune Algorithm.

Real-world applications of evolutionary computing (2000)
Presentation / Conference Contribution
Cagnoni, S., Poli, R., Smith, G. D., Corne, D., Oates, M., Hart, E., …Fogarty, T. C. (2000). Real-world applications of evolutionary computing. In Proceedings of EvoWorkshops 2000

This book constitutes the refereed proceedings of six workshops on evolutionary computation held concurrently as EvoWorkshops 2000 in Edinburgh, Scotland, UK, in April 2000. The 37 revised papers presented were carefully reviewed and selected by the... Read More about Real-world applications of evolutionary computing.

Enhancing the performance of a GA through visualisation. (2000)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2000). Enhancing the performance of a GA through visualisation. In Proceedings of GECCO-2000

This article describes a new tool for visualising genetic algorithms, (GAs) which is designed in order to allow the implicit mechanisms of the GA | i.e. crossover and mutation | to be thoroughly analysed. This allows the user to determine whether th... Read More about Enhancing the performance of a GA through visualisation..

Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem. (1999)
Journal Article
Hart, E., Ross, P., & Nelson, J. (1999). Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem. Annals of Operations Research, 92, 363-380. https://doi.org/10.1023/A%3A1018951218434

Genetic Algorithms (GAs) are a class of evolutionary algorithms that have been successfully applied to scheduling problems, in particular job-shop and flow-shop type problems where a number of theoretical benchmarks exist. This work applies a genet... Read More about Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem..

An immune system approach to scheduling in changing environments. (1999)
Presentation / Conference Contribution
Hart, E., & Ross, P. (1999). An immune system approach to scheduling in changing environments. In W. Banzhaf, J. M. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, & R. E. Smith (Eds.), GECCO-99 : proceedings of the genetic and evolutionary comp

This paper describes the application of an artificial immune system, (AIS), model to a scheduling application, in which sudden changes in the scheduling environment require the rapid production of new schedules. The model operates in two phases: In t... Read More about An immune system approach to scheduling in changing environments..

A heuristic combination method for solving job-shop scheduling problems. (1998)
Presentation / Conference Contribution
Hart, E., & Ross, P. (1998). A heuristic combination method for solving job-shop scheduling problems. In A. E. Eiben, T. Back, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature V (845-854). https://doi.org/10.1007/BFb0056926

This paper describes a heuristic combination based genetic algorithm, (GA), for tackling dynamic job-shop scheduling problems. Our approach is novel in that the genome encodes a choice of algorithm to be used to produce a set of schedulable operation... Read More about A heuristic combination method for solving job-shop scheduling problems..

Producing robust schedules via an artificial immune system. (1998)
Presentation / Conference Contribution
Hart, E., Ross, P., & Nelson, J. (1998). Producing robust schedules via an artificial immune system. In Proceedings of International Conference on Evolutionary Computing (464-469). https://doi.org/10.1109/ICEC.1998.699852

This paper describes an artificial immune system (AIS) approach to producing robust schedules for a dynamic jobshop scheduling problem in which jobs arrive continually, and the environment is subject to change due to practical reasons. We investi... Read More about Producing robust schedules via an artificial immune system..

A comparison of dominance mechanisms and simple mutation on non-stationary problems. (1998)
Presentation / Conference Contribution
Lewis, J., Hart, E., & Ritchie, G. (1998). A comparison of dominance mechanisms and simple mutation on non-stationary problems. In Parallel Problem Solving from Nature-PPSN V (139-148). https://doi.org/10.1007/BFb0056857

It is sometimes claimed that genetic algorithms using diploid representations will be more suitable for problems in which the environment changes from time to time, as the additional information stored in the double chromosome will ensure diversity,... Read More about A comparison of dominance mechanisms and simple mutation on non-stationary problems..

An adaptive mutation scheme for a penalty-based graph-colouring GA. (1998)
Presentation / Conference Contribution
Ross, P., & Hart, E. (1998). An adaptive mutation scheme for a penalty-based graph-colouring GA. In A. E. Eiben, T. Back, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature V (795-802). https://doi.org/10.1007/BFb0056921

The folklore of evolutionary algorithms still seems to contain some gross over-generalistions, such as that direct encodings are inferior to indirect ones, that penalty-function methods are often poor, and that observed performance on a few instances... Read More about An adaptive mutation scheme for a penalty-based graph-colouring GA..

Some observations about GA-based exam timetabling. (1998)
Presentation / Conference Contribution
Ross, P., Hart, E., & Corne, D. (1998). Some observations about GA-based exam timetabling. In E. Burke, & M. Carter (Eds.), Practice and Theory of Automated Timetabling II (115-129)

Although many people have tried using genetic algorithms (GAs) for exam timetabling, far fewer have done systematic investigations to try to determine whether a GA is a good choice of method or not. We have extensively studied GAs that use one partic... Read More about Some observations about GA-based exam timetabling..

Solving a real-world problem using an evolving heuristically driven schedule builder. (1998)
Journal Article
Hart, E., Ross, P., & Nelson, J. (1998). Solving a real-world problem using an evolving heuristically driven schedule builder. Evolutionary Computation, 6(1), 61-80. https://doi.org/10.1162/evco.1998.6.1.61

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be... Read More about Solving a real-world problem using an evolving heuristically driven schedule builder..