On the design of neuro-controllers for individual and social learning behaviour in autonomous robots: an evolutionary approach

Authors: Pini, Giovanni; Tuci, Elio

Source: Connection Science, Volume 20, Numbers 2-3, June 2008 , pp. 211-230(20)

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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).

Keywords: social learning; evolutionary robotics; autonomous robots; artificial neural networks

Document Type: Research article

DOI: http://dx.doi.org/10.1080/09540090802092014

Affiliations: 1: CoDE-IRIDIA, Universite Libre de Bruxelles (ULB), Bruxelles, Belgium

Publication date: 2008-06-01

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