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Linguistic Fuzzy-Logic Game Theory

Author

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  • Badredine Arfi

    (Department of Political Science, University of Florida, Gainesville)

Abstract

The author develops a new game-theoretic approach, anchored not in Boolean two-valued logic but instead in linguistic fuzzy logic. The latter is characterized by two key features. First, the truth values of logical propositions span a set of linguistic terms such as true , very true , almost false , very false , and false . Second, the logic allows logical categories to overlap in contrast to Boolean logic, where the two possible logical categories, “true†and “false,†are sharply distinct. A game becomes a linguistic fuzzy logic game by turning strategies into linguistic fuzzy strategies, players’ preferences into linguistic fuzzy preferences, and the rules of reasoning and inferences of the game into linguistic fuzzy reasoning operating according to linguistic fuzzy logic. This leads to the introduction of a new notion of linguistic fuzzy domination and linguistic Nash equilibrium.

Suggested Citation

  • Badredine Arfi, 2006. "Linguistic Fuzzy-Logic Game Theory," Journal of Conflict Resolution, Peace Science Society (International), vol. 50(1), pages 28-57, February.
    • Handle: RePEc:sae:jocore:v:50:y:2006:i:1:p:28-57
    DOI: 10.1177/0022002705284708
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    References listed on IDEAS

    as
    1. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773, September.
    2. Kydd, Andrew, 2000. "Trust, Reassurance, and Cooperation," International Organization, Cambridge University Press, vol. 54(2), pages 325-357, April.
    3. Arfi, Badredine, 2005. "Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA)," Political Analysis, Cambridge University Press, vol. 13(1), pages 23-56, January.
    4. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
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    Cited by:

    1. Badredine Arfi, 2009. "Probing the Democratic Peace Argument Using Linguistic Fuzzy Logic," International Interactions, Taylor & Francis Journals, vol. 35(1), pages 30-57, March.
    2. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 0. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 0, pages 1-17.
    3. Anjali Singh & Anjana Gupta, 2018. "Matrix Games with Interval-Valued 2-Tuple Linguistic Information," Games, MDPI, vol. 9(3), pages 1-19, September.
    4. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 2017. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 18(2), pages 131-147, June.

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