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Evolution of Hunter–Gatherer Strategies with a Genetically Inspired Algorithm

Author

Listed:
  • Pat Sutton

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

  • A. Georgallas

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

  • D. L. Hunter

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

  • N. Jan

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

  • R. J. Nash

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

  • J. P. Quinn

    (Physics Department, St. Francis Xavier University, Antigonish, Box 5000, Nova Scotia, Canada B2G 2W5, Canada)

Abstract

We address the following: Are there several optimal strategies for a hunter-gatherer society in a given environment, in which the society has an evolving level of technology and/or skills? We use the Genetic Algorithm, with point mutations, to facilitate the search for these strategies. We find that, in a generous environment, several optimal strategies are possible;there is no unique optimal strategy. We are now in a position, with the Genetic Algorithm, to assess different approaches to resource exploitation and the role of contingency.

Suggested Citation

  • Pat Sutton & A. Georgallas & D. L. Hunter & N. Jan & R. J. Nash & J. P. Quinn, 1998. "Evolution of Hunter–Gatherer Strategies with a Genetically Inspired Algorithm," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 9(04), pages 547-554.
    • Handle: RePEc:wsi:ijmpcx:v:09:y:1998:i:04:n:s0129183198000455
    DOI: 10.1142/S0129183198000455
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