Evolutionary Approaches to Improving the Layouts of Instance-Spaces
Conference Proceeding
Sim, K., & Hart, E. (2022)
Evolutionary Approaches to Improving the Layouts of Instance-Spaces. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (207-219). https://doi.org/10.1007/978-3-031-14714-2_15
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 in...
A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (2022)
A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (223-236). https://doi.org/10.1007/978-3-031-14714-2_16
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...
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...
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...
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...
WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets
Conference Proceeding
Pitt, J., Burth Kurka, D., Hart, E., & Cardoso, R. P. (2021)
WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets. In Applications of Evolutionary Computation: EvoApplications 2021 Proceedings. , (649-664). https://doi.org/10.1007/978-3-030-72699-7_41
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 ...
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training
Conference Proceeding
Panagiaris, N., Hart, E., & Gkatzia, D. (2020)
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training. In Proceedings of the 13th International Conference on Natural Language Generation. , (41-51
In this paper we consider the problem of optimizing neural Referring Expression Generation (REG) models with sequence level objectives. Recently reinforcement learning (RL) te...
Evolution of Diverse, Manufacturable Robot Body Plans
Conference Proceeding
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., …Tyrrell, A. M. (2020)
Evolution of Diverse, Manufacturable Robot Body Plans. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2132-2139). https://doi.org/10.1109/SSCI47803.2020.9308434
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 robot...