Using Simulated Annealing to Calculate the Trembles of Trembling Hand Perfection

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dc.creatorMcDonald, Stuart
dc.creatorWagner, Liam
dc.date2003-09-10
dc.date.accessioned2026-07-07T03:20:18Z
dc.date.available2026-07-07T03:20:18Z
dc.descriptionWithin the literature on non-cooperative game theory, there have been a number of attempts to propose logorithms which will compute Nash equilibria. Rather than derive a new algorithm, 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.
dc.descriptionTo appear in the Proceedings of IEEE Congress on Evolutionary Computation 2003 (CEC'03)
dc.identifierhttps://arxiv.org/abs/cs/0309016
dc.identifierhttp://arxiv.org/abs/cs/0309016
dc.identifierProceedings of IEEE Congress on Evolutionary Computation 2003, vol.4, pp. 2482-2489
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31781
dc.subjectComputer Science and Game Theory
dc.subjectComputational Complexity
dc.subjectData Structures and Algorithms
dc.subjectMachine Learning
dc.subjectNeural and Evolutionary Computing
dc.subjectPopulations and Evolution
dc.subjectF.1.1;F.2.2;G.3;I.2.1;J.4
dc.titleUsing Simulated Annealing to Calculate the Trembles of Trembling Hand Perfection
dc.typetext

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