Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers
Conference Proceeding
Cardoso, R. P., Hart, E., Burth Kurka, D., & Pitt, J. (2022)
Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers. In Applications of Evolutionary Computation: EvoApplications 2022 (418-434). https://doi.org/10.1007/978-3-031-02462-7_27
Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using grad...
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn
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). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9
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...
Morpho-evolution with learning using a controller archive as an inheritance mechanism
Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (in press)
Morpho-evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, https://doi.org/10.1109/tcds.2022.3148543
Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller ...
Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning
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.2021.0117
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...
Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models
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, https://doi.org/10.3389/fbuil.2021.745598
The construction and operation of buildings account for significant environmental impacts, including greenhouse gas (GHG) emissions, energy demand, resource consumption and wa...
A Neural Approach to Generation of Constructive Heuristics
Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2021)
A Neural Approach to Generation of Constructive Heuristics. In 2021 IEEE Congress on Evolutionary Computation (CEC) (1147-1154). https://doi.org/10.1109/CEC45853.2021.9504989
Both algorithm-selection methods and hyper-heuristic methods rely on a pool of complementary heuristics. Improving the pool with new heuristics can improve performance, howeve...
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics
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 doma...
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme
Conference Proceeding
Goff, L. K. L., & Hart, E. (2021)
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1498-1502). https://doi.org/10.1145/3449726.3463156
We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plan...
Using novelty search to explicitly create diversity in ensembles of classifiers
Conference Proceeding
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/10.1145/3449639.3459308
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...
Automated, Explainable Rule Extraction from MAP-Elites archives
Conference Proceeding
Urquhart, N., Höhl, S., & Hart, E. (2021)
Automated, Explainable Rule Extraction from MAP-Elites archives. In Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021. , (258-272). https://doi.org/10.1007/978-3-030-72699-7_17
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 f...