AutoMoDe-Pomodoro: An Evolutionary Class of Modular Designs

Nicolas Cambier, Eliseo Ferrante

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we reintroduce evolutionary algorithms into Auto-MoDe, an automatic design approach which optimizes behavioural modules into a probabilistic finite automaton. We evaluate three approaches, with different encodings of the probabilistic finite automaton phenotype, and observe their performances. This work opens modular designs to more advanced evolutionary robotics methods, such as novelty search and embodied evolution.

Original languageEnglish (US)
Title of host publicationGECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery, Inc
Pages100-103
Number of pages4
ISBN (Electronic)9781450392686
DOIs
StatePublished - Jul 9 2022
Event2022 Genetic and Evolutionary Computation Conference, GECCO 2022 - Virtual, Online, United States
Duration: Jul 9 2022Jul 13 2022

Publication series

NameGECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference

Conference

Conference2022 Genetic and Evolutionary Computation Conference, GECCO 2022
Country/TerritoryUnited States
CityVirtual, Online
Period7/9/227/13/22

Keywords

  • evolutionary robotics
  • genetic algorithm
  • modular design
  • swarm robotics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Computational Mathematics
  • Theoretical Computer Science

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