On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme
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...
WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets
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 ...
Evolution of Diverse, Manufacturable Robot Body Plans
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...
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019)
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147
The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the ...
Evolving robust policies for community energy system management
Cardoso, R., Hart, E., & Pitt, J. (2019)
Evolving robust policies for community energy system management. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (1120-1128). https://doi.org/10.1145/3321707.3321763
Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each p...
Algorithm selection using deep learning without feature extraction
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...
Use of machine learning techniques to model wind damage to forests
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...
Selection methods and diversity preservation in many-objective evolutionary algorithms
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...
Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018)
Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. In T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki, & H. Iizuka (Eds.), Proceedings of the 2018 Conference on Artificial Lifehttps://doi.org/10.1162/isal_a_00058
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'...
A new rich vehicle routing problem model and benchmark resource
Sim, K., Hart, E., Urquhart, N. B., & Pigden, T. (2018)
A new rich vehicle routing problem model and benchmark resource. In Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. https://doi.org/10.1007/978-3-319-89988-6_30
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 characteri...