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All Outputs (93)

A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control (2024)
Conference Proceeding
Montague, K., Hart, E., & Paechter, B. (2024). A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (178-193). https://doi.org/10.1007/978-3-031-56852-7_12

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.

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Conference Proceeding
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 European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (145-160). https://doi.org/10.1007/978-3-031-30229-9_10

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.

On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture (2023)
Conference Proceeding
Lupión, M., Cruz, N. C., Paechter, B., & Ortigosa, P. M. (2023). On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture. In Metaheuristics: 14th International Conference, MIC 2022, Syracuse, Italy, July 11–14, 2022, Proceedings (133-142). https://doi.org/10.1007/978-3-031-26504-4_10

Neural networks stand out in Artificial Intelligence for their capacity of being applied to multiple challenging tasks such as image classification. However, designing a neural network to address a particular problem is also a demanding task that req... Read More about On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture.

Accelerating neural network architecture search using multi-GPU high-performance computing (2022)
Journal Article
Lupión, M., Cruz, N. C., Sanjuan, J. F., Paechter, B., & Ortigosa, P. M. (2023). Accelerating neural network architecture search using multi-GPU high-performance computing. Journal of Supercomputing, 79, 7609-7625. https://doi.org/10.1007/s11227-022-04960-z

Neural networks stand out from artificial intelligence because they can complete challenging tasks, such as image classification. However, designing a neural network for a particular problem requires experience and tedious trial and error. Automating... Read More about Accelerating neural network architecture search using multi-GPU high-performance computing.

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/10.1007/978-3-030-72069-8_6

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.

Evolving planar mechanisms for the conceptual stage of mechanical design (2019)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019). Evolving planar mechanisms for the conceptual stage of mechanical design. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (383-384). https://doi.org/10.1145/3319619.3322006

This study presents a method to evolve planar mechanism prototypes using an evolutionary computing approach. Ultimately, the idea is to provide drafts for designers at the conceptual design stage of mechanism design which meet their design brief. The... Read More about Evolving planar mechanisms for the conceptual stage of mechanical design.

Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes (2019)
Journal Article
Ferrández, M. R., Redondo, J. L., Ivorra, B., Ramos, A. M., Ortigosa, P. M., & Paechter, B. (2020). Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes. Engineering Optimization, 52(5), 896-913. https://doi.org/10.1080/0305215x.2019.1618289

This work focuses on the optimization of some high-pressure and temperature food treatments. In some cases, when dealing with real-life multi-objective optimization problems, such as the one considered here, the computational cost of evaluating the c... Read More about Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes.

2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms (2018)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019). 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. In H. Rodrigues, J. Herskovits, C. Mota Soares, A. Araújo, J. Guedes, J. Folgado, …J. Madeira (Eds.), EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization (926-937). https://doi.org/10.1007/978-3-319-97773-7_80

In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A specific area of mechanical design focuses on planar mechanisms. These are a... Read More about 2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms.

On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains (2018)
Conference Proceeding
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 8–12, 2018, Proceedings, Part I. https://doi.org/10.1007/978-3-319-99253-2_14

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.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Conference Proceeding
Hart, E., Steyven, A. S. W., & Paechter, B. (2018). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. In GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference (101-108). https://doi.org/10.1145/3205455.3205481

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)
Conference Proceeding
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). https://doi.org/10.1007/978-3-319-77538-8_40

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.

Evaluation of a genetic representation for outline shapes (2017)
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2017). Evaluation of a genetic representation for outline shapes. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion (1419-1422). https://doi.org/10.1145/3067695.3082501

This work in progress focuses on the evaluation of a genetic representation for outline shapes for planar mechanical levers which addresses the first stage of the complex real-world problem of modelling and evolving planar mechanical lever systems. T... Read More about Evaluation of a genetic representation for outline shapes.

On the comparison of initialisation strategies in differential evolution for large scale optimisation (2017)
Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018). On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z

Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works have studied the effects that a population initialisation strategy has on... Read More about On the comparison of initialisation strategies in differential evolution for large scale optimisation.

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics (2017)
Conference Proceeding
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). https://doi.org/10.1145/3071178.3071232

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)
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016). Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016 (296-305). https://doi.org/10.1007/978-3-319-50349-3_25

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)
Conference Proceeding
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 (CEC). https://doi.org/10.1109/CEC.2016.7743969

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.

Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things (2016)
Conference Proceeding
Ghaleb, B., Al-Dubai, A., Ekonomou, E., Paechter, B., & Qasem, M. (2016). Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things. In Wireless Communications and Networking Conference (WCNC), 2016 IEEE (1-6). https://doi.org/10.1109/WCNC.2016.7564654

Constrained Low-power and Lossy networks (LLNs) represent the building block for the ever-growing Internet of Things (IoT) that deploy the Routing Protocol for Low Power and Lossy networks (RPL) as a key routing standard. RPL, along with other routin... Read More about Trickle-Plus: Elastic Trickle algorithm for Low-power networks and Internet of Things.

Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm (2016)
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2016). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In Parallel Problem Solving from Nature – PPSN XIV; Lecture Notes in Computer Science (921-931). https://doi.org/10.1007/978-3-319-45823-6_86

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.

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems (2016)
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV (134-144). https://doi.org/10.1007/978-3-319-45823-6_13

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.

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. (2015)
Conference Proceeding
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 Evolutionary Computation Conference - GECCO '15 (169-176). https://doi.org/10.1145/2739480.2754688

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..