Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language
Conference Proceeding
Urquhart, N., & Hunter, K. (2024)
Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation (83–97). https://doi.org/10.1007/978-3-031-56852-7_6
When using a meta-heuristic based optimiser in some industrial scenarios, there may be a need to amend the objective function as time progresses to encompass constraints that ...
Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation Expensive Bi-Objective
Conference Proceeding
Rodriguez, C. J., Thomson, S. L., Alderliesten, T., & Bosman, P. A. N. (in press)
Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation Expensive Bi-Objective. . https://doi.org/10.1145/3638529.3654125
Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle suc...
Understanding fitness landscapes in morpho-evolution via local optima networks
Conference Proceeding
Thomson, S. L., Le Goff, L., Hart, E., & Buchanan, E. (in press)
Understanding fitness landscapes in morpho-evolution via local optima networks. . https://doi.org/10.1145/3638529.3654059
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 h...
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press)
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028
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 mach...
A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control
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 a...
On the Utility of Probing Trajectories for Algorithm-Selection
Conference Proceeding
Renau, Q., & Hart, E. (2024)
On the Utility of Probing Trajectories for Algorithm-Selection. In Applications of Evolutionary Computation. EvoApplications 2024 (98-114). https://doi.org/10.1007/978-3-031-56852-7_7
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 desc...
Generalized Early Stopping in Evolutionary Direct Policy Search
Journal Article
Arza, E., Le Goff, L. K., & Hart, E. (in press)
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...
Design and Evaluation of Memory Efficient Data Structure Scheme for Energy Drainage Attacks in Wireless Sensor Networks
Journal Article
Bhatti, D. S., Saleem, S., Ali, Z., Park, T., Suh, B., Kamran, A., …Kim, K. (2024)
Design and Evaluation of Memory Efficient Data Structure Scheme for Energy Drainage Attacks in Wireless Sensor Networks. IEEE Access, 12, 41499-41516. https://doi.org/10.1109/access.2024.3377144
Wireless Sensor Networks (WSN) are deployed on a large scale and require protection from malicious energy drainage attacks, particularly those directed at the routing layer. T...
Cluster-based oversampling with area extraction from representative points for class imbalance learning
Journal Article
Farou, Z., Wang, Y., & Horváth, T. (2024)
Cluster-based oversampling with area extraction from representative points for class imbalance learning. Intelligent Systems with Applications, 22, Article 200357. https://doi.org/10.1016/j.iswa.2024.200357
Class imbalance learning is challenging in various domains where training datasets exhibit disproportionate samples in a specific class. Resampling methods have been used to a...
Information flow and Laplacian dynamics on local optima networks
Conference Proceeding
Richter, H., & Thomson, S. L. (in press)
Information flow and Laplacian dynamics on local optima networks.
We propose a new way of looking at local optima networks (LONs). LONs represent fitness landscapes; the nodes are local optima, and the edges are search transitions between th...