Evolving collective behaviours in simulated kilobots
Pages 824 - 831
Abstract
The field of Evolutionary Robotics has multiple common tasks and widely used benchmark activities such as navigation, obstacle avoidance, and phototaxis. We present an evolutionary approach to learning behaviours that demonstrate emergent collective phototaxis in a swarm of simulated robots.
Our approach demonstrates that evolutionary computation can be used to evolve the emergent, self-organising behaviours of clustering and phototaxis in a population of simulated robots where the robots possess limited capabilities. In addition to demonstrating the feasibility of the approach, we show that the evolved behaviours are also robust to noise and flexible in changing environments.
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Index Terms
- Evolving collective behaviours in simulated kilobots
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Published In
April 2018
2327 pages
ISBN:9781450351911
DOI:10.1145/3167132
- Conference Chairs:
- Hisham M. Haddad,
- Roger L. Wainwright,
- Richard Chbeir
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Published: 09 April 2018
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