Evolution of Hunter–Gatherer Strategies with a Genetically Inspired Algorithm

Pat Sutton, A. Georgallas, D. L. Hunter, N. Jan, R. J. Nash and J. P. Quinn
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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

International Journal of Modern Physics C (IJMPC), 1998, vol. 09, issue 04, 547-554

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.

Keywords: Hunter-Gatherer; Evolutionary Skills; Genetic Algorithm; Optimal Strategies (search for similar items in EconPapers)
Date: 1998
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DOI: 10.1142/S0129183198000455

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