Energy and Complexity in Evolving Collective Robot Bodies and Brains

Hallauer, S and Nitschke, G (2020) Energy and Complexity in Evolving Collective Robot Bodies and Brains, Proceedings of IEEE Congress on Evolutionary Computation (IEEE CEC 2020).

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Abstract

The impact of the environment on evolving increasingly complex morphologies (bodies) and controllers (brains) remains an open question in evolutionary biology and has important implications for the evolutionary design of robots. This study uses evolutionary robotics as an experimental platform to evaluate relationships between environment complexity and evolving bodybrain complexity given energy costs on evolving complexity. We evolve robot body-brain designs for increasingly complex environments (difficult cooperative transport tasks) in a collective robotic gathering simulation. The impact of complexity costs on body-brain evolution is evaluated across such increasingly complex environments. Results indicate that complexity costs enable the evolution of simpler body-brain designs that are effective in simple environments but yield negligible behavior (task performance) differences in more complex environments.

Item Type: Conference paper
Subjects: Computing methodologies > Machine learning
Date Deposited: 03 Dec 2021 11:14
Last Modified: 03 Dec 2021 11:14
URI: https://pubs.cs.uct.ac.za/id/eprint/1484

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