  Within 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.
