2007
DOI: 10.1016/j.jet.2005.12.010
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Brown's original fictitious play

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2008
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Cited by 70 publications
(44 citation statements)
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“…In evolutionary game theory, this problem is addressed by developing dynamic learning models that converge to the equilibria [24]. One of the simplest classes of such learning models is fictitious play [25][26][27]. In fictitious play, it is assumed that the other player plays with a stationary strategy, which is estimated by the hitherto observed empirical choice frequencies.…”
Section: A Risk-sensitive Model Of Interactionmentioning
confidence: 99%
“…In evolutionary game theory, this problem is addressed by developing dynamic learning models that converge to the equilibria [24]. One of the simplest classes of such learning models is fictitious play [25][26][27]. In fictitious play, it is assumed that the other player plays with a stationary strategy, which is estimated by the hitherto observed empirical choice frequencies.…”
Section: A Risk-sensitive Model Of Interactionmentioning
confidence: 99%
“…An ǫ-saddle-point for (20) is an ǫ-equilibrium for this game. One could, in principle, use fictitious play [4] or similar methods to compute such an ǫ-equilibrium. Since the general methods for computing ǫ-equilibria in minimax games rely on subgradient descent and the primaldual objective functions are non-smooth, these general methods need O(ǫ −2 ) iterations to converge [34].…”
Section: Solving the Saddle-point Problemmentioning
confidence: 99%
“…For more recent results on the issue of convergence and nonconvergence of fictitious play and the best response dynamics see Berger (2005Berger ( , 2007aBerger ( , 2007bBerger ( , 2008, Hofbauer and Sandholm (2009), Hahn (2010), and van Strien (2011).…”
Section: Introductionmentioning
confidence: 99%