On the Design of Neuro-controllers for Individual and Social Learning Behaviour in Autonomous Robots: An Evolutionary Approach

Giovanni Pini, Elio Tuci

Research output: Contribution to journalSpecial issuepeer-review

10 Citations (SciVal)

Abstract

In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis).
Original languageEnglish
Pages (from-to)211-230
Number of pages20
JournalConnection Science
Volume20
Issue number2-3
DOIs
Publication statusPublished - 01 Mar 2008

Keywords

  • social learning
  • evolutionary robotics
  • autonomous robots
  • artificial neural networks

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