Spanellis, C and Stewart, B and Nitschke, G (2021) The Environment and Body-Brain Complexity, Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2021).
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Abstract
An open question for both natural and artificial evolutionary systems is how, and under what environmental and evolutionary conditions complexity evolves. This study investigates the impact of increasingly complex task environments on the evolution of robot complexity. Specifically, the impact of evolving body-brain couplings on locomotive task performance, where robot evolution was directed by either body-brain exploration (novelty search) or objective-based (fitness function) evolutionary search. Results indicated that novelty search enabled the evolution of increased robot body-brain complexity and efficacy given specific environment conditions. The key contribution is thus the demonstration that body-brain exploration is suitable for evolving robot complexity that enables high fitness robots in specific environments.
| Item Type: | Conference paper |
|---|---|
| Subjects: | Computing methodologies > Machine learning |
| Date Deposited: | 03 Dec 2021 11:20 |
| Last Modified: | 03 Dec 2021 11:20 |
| URI: | https://pubs.cs.uct.ac.za/id/eprint/1492 |
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