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Using Artificial Intelligence Techniques for Strategy Generation in the Commons Game

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Hybrid Artificial Intelligent Systems (HAIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6678))

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Abstract

In this paper, we consider the use of artificial intelligence techniques to aid in discovery of winning strategies for the Commons Game (CG).

The game represents a common scenario in which multiple parties share the use of a self-replenishing resource. The resource deteriorates quickly if used indiscriminately. If used responsibly, however, the resource thrives. We consider the scenario one player uses hill climbing or particle swarm optimization to select the course of action, while the remaining Nā€‰āˆ’ā€‰1 players use a fixed probability vector. We show that hill climbing and particle swarm optimization consistently generate winning strategies.

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Author information

Authors and Affiliations

  1. School of Computer Science, Carleton University, Ottawa, Canada

    Petro Verkhogliad

  2. IEEE and IAPR, School of Computer Science, Carleton University, Ottawa, Canada

    B. John Oommen

  3. University of Agder in Grimstad, Norway

    B. John Oommen

Authors
  1. Petro Verkhogliad
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  2. B. John Oommen
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Editor information

Editors and Affiliations

  1. GICAP Research Group, University of Burgos, 09006, Burgos, Spain

    Emilio Corchado

  2. Wroclaw University of Technology, 50-370, Wroclaw, Poland

    Marek Kurzyński  & Michał WoÅŗniak  & 

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Verkhogliad, P., Oommen, B.J. (2011). Using Artificial Intelligence Techniques for Strategy Generation in the Commons Game . In: Corchado, E., Kurzyński, M., WoÅŗniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21219-2_7

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  • DOI: https://doi.org/10.1007/978-3-642-21219-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21218-5

  • Online ISBN: 978-3-642-21219-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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