Publikation: Diversity in swarm robotics with task-independent behavior characterization
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2020
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COELLO COELLO, Carlos Artemio, ed.. GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. New York, NY: ACM, 2020, pp. 83-84. ISBN 978-1-4503-7127-8. Available under: doi: 10.1145/3377929.3389949
Zusammenfassung
Evolutionary computation provides methods to automatically generate controllers for swarm robotics. Many approaches rely on optimization and the targeted behavior is quantified in form of a fitness function. Other methods, like novelty search, increase exploration by putting selective pressure on unexplored behavior space using a domain-specific behavioral distance function. In contrast, minimize surprise leads to the emergence of diverse behaviors by using an intrinsic motivation as fitness, that is, high prediction accuracy. We compare a standard genetic algorithm, novelty search and minimize surprise in a swarm robotics setting to evolve diverse behaviors and show that minimize surprise is competitive to novelty search.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
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behavioral diversity, evolutionary robotics, swarm robotics
Konferenz
GECCO '20 : Genetic and Evolutionary Computation Conference, 8. Juli 2020 - 12. Juli 2020, Cancún, Mexico
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KAISER, Tanja Katharina, Heiko HAMANN, 2020. Diversity in swarm robotics with task-independent behavior characterization. GECCO '20 : Genetic and Evolutionary Computation Conference. Cancún, Mexico, 8. Juli 2020 - 12. Juli 2020. In: COELLO COELLO, Carlos Artemio, ed.. GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. New York, NY: ACM, 2020, pp. 83-84. ISBN 978-1-4503-7127-8. Available under: doi: 10.1145/3377929.3389949BibTex
@inproceedings{Kaiser2020Diver-59736,
year={2020},
doi={10.1145/3377929.3389949},
title={Diversity in swarm robotics with task-independent behavior characterization},
isbn={978-1-4503-7127-8},
publisher={ACM},
address={New York, NY},
booktitle={GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion},
pages={83--84},
editor={Coello Coello, Carlos Artemio},
author={Kaiser, Tanja Katharina and Hamann, Heiko}
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