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Outputs (57)

Image Based Proximate Shadow Retargeting (2018)
Presentation / Conference Contribution
Casas, L., Fauconneau, M., Kosek, M., Mclister, K., & Mitchell, K. (2018, September). Image Based Proximate Shadow Retargeting. Presented at Computer Graphics & Visual Computing (CGVC) 2018, Swansea University, United Kingdom

We introduce Shadow Retargeting which maps real shadow appearance to virtual shadows given a corresponding deformation of scene geometry, such that appearance is seamlessly maintained. By performing virtual shadow reconstruction from un-occluded real... Read More about Image Based Proximate Shadow Retargeting.

Home appliances classification based on multi-feature using ELM (2018)
Journal Article
Wu, Z., Liu, Q., Chen, F., Chen, F., Liu, X., & Linge, N. (2018). Home appliances classification based on multi-feature using ELM. International Journal of Sensor Networks, 28(1), 34. https://doi.org/10.1504/ijsnet.2018.094710

With the development of science and technology, the application in artificial intelligence has been more and more popular, as well as smart home has become a hot topic. And pattern recognition adapting to smart home attracts more attention, while the... Read More about Home appliances classification based on multi-feature using ELM.

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, September). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. Presented at Fifteenth International Conference on Parallel Problem Solving from Nature (PPSN XV), Coimbra, Portugal

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.

A Transparent Thread and Fiber Framework in C++CSP (2018)
Presentation / Conference Contribution
Chalmers, K. (2018, August). A Transparent Thread and Fiber Framework in C++CSP. Presented at Communicating Process Architectures, Dresden, Germany

There are multiple low-level concurrency primitives supported today, but these often require the programmer to be explicit in their implementation decisions at design time. This work illustrates how a process-oriented model written in C++CSP can hide... Read More about A Transparent Thread and Fiber Framework in C++CSP.

GPU-accelerated depth codec for real-time, high-quality light field reconstruction (2018)
Journal Article
Koniaris, B., Kosek, M., Sinclair, D., & Mitchell, K. (2018). GPU-accelerated depth codec for real-time, high-quality light field reconstruction. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(1), 1-15. https://doi.org/10.1145/3203193

Pre-calculated depth information is essential for efficient light field video rendering, due to the prohibitive cost of depth estimation from color when real-time performance is desired. Standard state-of-the-art video codecs fail to satisfy such per... Read More about GPU-accelerated depth codec for real-time, high-quality light field reconstruction.

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 Applications to Industrial and Societal Problems, EUROGEN-2015, University of Strathclyde, Glasgow

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.

Modelling enduring institutions: The complementarity of evolutionary and agent-based approaches (2018)
Journal Article
Powers, S. T., Ekárt, A., & Lewis, P. R. (2018). Modelling enduring institutions: The complementarity of evolutionary and agent-based approaches. Cognitive Systems Research, 52, 67-81. https://doi.org/10.1016/j.cogsys.2018.04.012

Empirical work has shown that societies can sometimes avoid antisocial outcomes , such as the Tragedy of the Commons, by establishing institutional rules that govern their interactions. Moreover, groups are more likely to avoid antisocial outcomes wh... Read More about Modelling enduring institutions: The complementarity of evolutionary and agent-based approaches.

Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces. (2018)
Presentation / Conference Contribution
Bamgboye, O., Liu, X., & Cruickshank, P. (2018, July). Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces. Presented at 12th IEEE Interna@onal Workshop on QUALITY ORIENTED REUSE OF SOFTWARE" (QUORS 2018)/ 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Tokyo, Japan

Smart Spaces currently benefits from Internet of Things (IoT) infrastructures in order to realise its objectives. In many cases, it demonstrates this through certain automated applications that relies on sensor streams that comes with some uncertaint... Read More about Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces..

Towards reducing complexity of multi-agent simulations by applying model-driven techniques (2018)
Presentation / Conference Contribution
Hoffman, B., Chalmers, K., Urquhart, N., Farrenkopf, T., & Guckert, M. (2018, June). Towards reducing complexity of multi-agent simulations by applying model-driven techniques. Presented at International Conference on Practical Applications of Agents and Multi-Agent Systems PAAMS 2018, Toledo, Spain

Creating multi-agent simulations is a challenging task often requiring programming skills at the professional software developer level. Model driven methods of software development are an appropriate tool for reducing the complexity of the developmen... Read More about Towards reducing complexity of multi-agent simulations by applying model-driven techniques.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (2018)
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018). Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), Article 2383. https://doi.org/10.1038/s41467-018-04316-3

Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-... Read More about Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

Using a task classification in the visualisation design process for task understanding and abstraction: an empirical study (2018)
Presentation / Conference Contribution
Kerracher, N., Kennedy, J., & Chalmers, K. (2018, June). Using a task classification in the visualisation design process for task understanding and abstraction: an empirical study. Presented at Eurographics Conference on Visualization (EuroVis)

Task classifications are widely purported to be useful in the design process, with various suggestions having been made for their use at the different stages. However, little has been written regarding the actual use of task classifications in these... Read More about Using a task classification in the visualisation design process for task understanding and abstraction: an empirical study.

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (2018)
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169

Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward... Read More about An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0.

A Domain-Specific Language For Routing Problems (2018)
Presentation / Conference Contribution
Hoffmann, B., Guckert, M., Farrenkopf, T., Chalmers, K., & Urquhart, N. (2018, May). A Domain-Specific Language For Routing Problems. Presented at 32nd Conference on Modelling and Simulation

Vehicle Routing Problems (VRPs) are commonly used as benchmark optimisation problems and they also have many applications in industry. Using agent-based approaches to solve VRPs allows the analysis of dynamic VRP instances that incorporate congestion... Read More about A Domain-Specific Language For Routing Problems.