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Intelligent Versus Random Beavers—an Agent‐Based Approach in Facing the Busy Beaver Problem

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  • Alessandro Perrone
  • Gianluigi Ferraris

Abstract

Since Tibor Rado in 1962 defined the busy beaver game, several approaches have used computer technology to search for ‘best’ candidates to solve it. In this paper we follow an ‘evolutionary approach’ to solving it using agent‐based techniques. This approach includes techniques to reduce the number of inspected Turing machines and to accelerate simulation of Turing machines using agent‐based techniques; in particular we use the ‘Swarm simulation toolkit’. Our approach uses a variety of learning techniques such as genetic algorithms, classifier systems multiple genetic algorithms and random search to explore the universe of the ‘best solution’ to the game.

Suggested Citation

  • Alessandro Perrone & Gianluigi Ferraris, 2004. "Intelligent Versus Random Beavers—an Agent‐Based Approach in Facing the Busy Beaver Problem," Metroeconomica, Wiley Blackwell, vol. 55(2‐3), pages 332-344, May.
    • Handle: RePEc:bla:metroe:v:55:y:2004:i:2-3:p:332-344
    DOI: 10.1111/j.0026-1386.2004.00196.x
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    References listed on IDEAS

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    1. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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