Gagen, Michael and Nemoto, Kae (2006): Variational optimization of probability measure spaces resolves the chain store paradox.
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Abstract
In game theory, players have continuous expected payoff functions and can use fixed point theorems to locate equilibria. This optimization method requires that players adopt a particular type of probability measure space. Here, we introduce alternate probability measure spaces altering the dimensionality, continuity, and differentiability properties of what are now the game's expected payoff functionals. Optimizing such functionals requires generalized variational and functional optimization methods to locate novel equilibria. These variational methods can reconcile game theoretic prediction and observed human behaviours, as we illustrate by resolving the chain store paradox. Our generalized optimization analysis has significant implications for economics, artificial intelligence, complex system theory, neurobiology, and biological evolution and development.
Item Type: | MPRA Paper |
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Institution: | University of Queensland |
Original Title: | Variational optimization of probability measure spaces resolves the chain store paradox |
Language: | English |
Keywords: | optimization; probability measure space; noncooperative game; chain store paradox |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C72 - Noncooperative Games |
Item ID: | 4778 |
Depositing User: | Michael Gagen |
Date Deposited: | 08 Sep 2007 |
Last Modified: | 28 Sep 2019 15:22 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/4778 |