Using Simulated Annealing to Calculate the Trembles of Trembling Hand Perfection
Stuart McDonald () and
MPRA Paper from University Library of Munich, Germany
Within the literature on non-cooperative game theory, there have been a number of algorithms which will compute Nash equilibria. This paper shows that the family of algorithms known as Markov chain Monte Carlo (MCMC) can be used to calculate Nash equilibria. MCMC is a type of Monte Carlo simulation that relies on Markov chains to ensure its regularity conditions. MCMC has been widely used throughout the statistics and optimization literature, where variants of this algorithm are known as simulated annealing. This paper shows that there is interesting connection between the trembles that underlie the functioning of this algorithm and the type of Nash refinement known as trembling hand perfection. This paper shows that it is possible to use simulated annealing to compute this refinement.
Keywords: Trembling Hand Perfection; Equilibrium Selection and Computation; Simulated Annealing; Markov Chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: C72 C73 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:89127
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