Abstract
The fuzzy preference is related to decision making in artificial intelligence. A mathematical model for dynamic and stochastic decision making together with perception and cognition is presented. This paper models human behavior based on the aggregated fuzzy preferences, and an objective function induced from the fuzzy preferences is formulated. In dynamic decision making, there exists a difficulty when we formulate the objective function from fuzzy preferences since the value criterion of fuzzy preferences in dynamic behavior transforms together with time and it is formulated gradually based on the experience. A reasonable criterion based on fuzzy preferences is formulated for the dynamic decision making, and an optimality equation for this model is derived by dynamic programming. Mathematical models to simulate human behavior with his decision making are applicable to various fields: robotics, customers’ behavior analysis in marketing, multi-agent systems and so on.
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Yoshida, Y. (2004). Decision Making in a Dynamic System Based on Aggregated Fuzzy Preferences. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2004. Lecture Notes in Computer Science(), vol 3131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27774-3_23
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DOI: https://doi.org/10.1007/978-3-540-27774-3_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22555-3
Online ISBN: 978-3-540-27774-3
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