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Genome Variations

Effects on the Robustness of Neuroevolved Control for Swarm Robotics Systems
  • Pedro Romano
  • Luís NunesEmail author
  • Anders Lyhne Christensen
  • Miguel Duarte
  • Sancho Moura Oliveira
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 417)

Abstract

Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and benefit swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.

Keywords

Neuroevolution Robot controllers Genome Variations Swarm robotics Robustness Heterogeneity 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pedro Romano
    • 1
  • Luís Nunes
    • 1
    Email author
  • Anders Lyhne Christensen
    • 1
  • Miguel Duarte
    • 1
  • Sancho Moura Oliveira
    • 1
  1. 1.Instituto de TelecomunicaçõesInstituto Universitário de Lisboa (ISCTE-IUL)LisboaPortugal

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