Connectionist Learning in Behaviour-Based Mobile Robots: A Survey

  • Authors:
  • Mark Rylatt;Chris Czarnecki;Tom Routen

  • Affiliations:
  • Department of Computer Science, De Montfort University, Leicester LE1 9BH U.K. E-mail: Email: rylatt@dmu.ac.uk;Department of Computer Science, De Montfort University, Leicester LE1 9BH U.K. E-mail: Email: cc@dmu.ac.uk;Department of Computer Science, De Montfort University, Leicester LE1 9BH U.K. E-mail: Email: twr@dmu,ac.uk

  • Venue:
  • Artificial Intelligence Review
  • Year:
  • 1998

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Abstract

This paper is a survey of some recentconnectionist approaches to the design and developmentof behaviour-based mobile robots. The research isanalysed in terms of principal connectionist learningmethods and neurological modeling trends. Possibleadvantages over conventionally programmed methods areconsidered and the connectionist achievements to dateare assessed. A realistic view is taken of theprospects for medium term progress and someobservations are made concerning the direction thismight profitably take.