A Class of Two-Person Zero-Sum Matrix Games with Rough Payoffs | Zendy

Jiuping Xu | Zendy; Liming Yao | Zendy

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A Class of Two-Person Zero-Sum Matrix Games with Rough Payoffs

Author(s) -

Jiuping Xu,

Liming Yao

Publication year - 2010

Publication title -

international journal of mathematics and mathematical sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.21

H-Index - 39

eISSN - 1687-0425

pISSN - 0161-1712

DOI - 10.1155/2010/404792

Subject(s) - minimax , class (philosophy) , mathematics , operator (biology) , zero (linguistics) , zero sum game , matrix (chemical analysis) , measure (data warehouse) , value (mathematics) , mathematical economics , combinatorics , algorithm , mathematical optimization , discrete mathematics , computer science , game theory , artificial intelligence , statistics , data mining , biochemistry , chemistry , linguistics , philosophy , materials science , repressor , transcription factor , composite material , gene

We concentrate on discussing a class of two-person zero-sumgames with rough payoffs. Based on the expected value operator and the trust measure ofrough variables, the expected equilibrium strategy and r-trust maximin equilibrium strategy aredefined. Five cases whether the game exists r-trust maximin equilibrium strategy are discussed,and the technique of genetic algorithm is applied to find the equilibrium strategies. Finally, anumerical example is provided to illustrate the practicality and effectiveness of the proposedtechnique

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