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Designing good pursuit problems as testbeds for distributed AI: A novel application of genetic algorithms

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Book cover From Reaction to Cognition (MAAMAW 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 957))

Abstract

A basic N x M instance (game) of the Pursuit Problem is one in which N pursuing agents try to capture as many as possible of M prey agents by surrounding them, on a rectilinear grid. The 4 × 1 game has been considered as a testbed for comparing the effectiveness of different multiagent distributed architectures, and the 6 × 2 game has received a little attention. This paper reports a systematic exercise in evaluating the quality of pursuit games as potential testbeds for distributed artificial intelligence (DAI). Genetic algorithms (GAs) have been used both to optimise low-level architectural features of agents and to search the (N, M) space of games. The conclusion from experiments is that (M + 4) × M games have the right complexity to be good testbeds, provided that M > 4. Additionally, the paper demonstrates the usefulness of GAs as tools to help DAI designers, and argues that boredom is a concept that deserves consideration as a feature of general agent architectures.

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Authors and Affiliations

  1. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, England

    Mauro Manela & J. A. Campbell

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  1. Mauro Manela
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  2. J. A. Campbell
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Cristiano Castelfranchi Jean-Pierre Müller

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© 1995 Springer-Verlag Berlin Heidelberg

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Manela, M., Campbell, J.A. (1995). Designing good pursuit problems as testbeds for distributed AI: A novel application of genetic algorithms. In: Castelfranchi, C., Müller, JP. (eds) From Reaction to Cognition. MAAMAW 1993. Lecture Notes in Computer Science, vol 957. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027067

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  • DOI: https://doi.org/10.1007/BFb0027067

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60155-5

  • Online ISBN: 978-3-540-49532-1

  • eBook Packages: Springer Book Archive

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