Minimize surprise MAP-elites : a task-independent MAP-elites variant for swarms

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FIELDSEND, Jonathan E., ed.. GECCO '22 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, NY: ACM, 2022, pp. 116-119. ISBN 978-1-4503-9268-6. Available under: doi: 10.1145/3520304.3528773
Zusammenfassung

Swarm robotics controllers are often automatically generated using methods of evolutionary computation with a task-specific fitness function to guide the optimization process. By contrast, our minimize surprise approach uses a task-independent fitness function to generate diverse behaviors over several independent evolutionary runs. Alternatives are divergent search algorithms rewarding behavioral novelty, such as novelty search, and quality-diversity algorithms generating diverse high-quality solutions, such as MAP-Elites. These approaches usually rely on task-dependent measures. We propose Minimize Surprise MAP-Elites, a task-independent MAP-Elites variant that combines MAP-Elites with our minimize surprise approach. Our first experiments result in high-quality solutions that lead to behavioral diversity across tasks and within tasks.

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GECCO '22 : Genetic and Evolutionary Computation Conference, 9. Juli 2022 - 13. Juli 2022, Boston, MA, USA
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ISO 690KAISER, Tanja Katharina, Heiko HAMANN, 2022. Minimize surprise MAP-elites : a task-independent MAP-elites variant for swarms. GECCO '22 : Genetic and Evolutionary Computation Conference. Boston, MA, USA, 9. Juli 2022 - 13. Juli 2022. In: FIELDSEND, Jonathan E., ed.. GECCO '22 : Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, NY: ACM, 2022, pp. 116-119. ISBN 978-1-4503-9268-6. Available under: doi: 10.1145/3520304.3528773
BibTex
@inproceedings{Kaiser2022Minim-59705,
  year={2022},
  doi={10.1145/3520304.3528773},
  title={Minimize surprise MAP-elites : a task-independent MAP-elites variant for swarms},
  isbn={978-1-4503-9268-6},
  publisher={ACM},
  address={New York, NY},
  booktitle={GECCO '22 : Proceedings of the Genetic and Evolutionary Computation Conference Companion},
  pages={116--119},
  editor={Fieldsend, Jonathan E.},
  author={Kaiser, Tanja Katharina and Hamann, Heiko}
}
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