Abstract
According to the features of fuzzy information, we put forward the concept of level effect function L(λ), established a very practical and workable measurement method I L – which can quantify the location of fuzzy number intensively and globally, and set up the level of uncertainty for measurement I L – under the level effect function L(λ). Thus we can improve the fuzzy bimatrix game. For this problem, after establishing the model involving fuzzy variable and fuzzy coefficient for each player, we introduced the theory of modern biological gene into equilibrium solution calculation of game, then designed the genetic algorithm model for solving Nash equilibrium solution of fuzzy bimatrix game and proved the validity of the algorithm by the examples of bimatrix game. It will lay a theoretical foundation for uncertain game under some consciousness and have strong maneuverability.
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© 2007 Springer-Verlag Berlin Heidelberg
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Wang, R., Jiang, J., Zhu, X. (2007). Improved Genetic Algorithms to Fuzzy Bimatrix Game. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_66
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DOI: https://doi.org/10.1007/978-3-540-74205-0_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74201-2
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