Searching for Nash Equilibrium in bimatrix games is a challenging problem. The Lemke-Howson algorithm addresses this problem using linear programming tools, and its theoretical time complexity can even be exponential.
In this thesis, we present the mathematical background of the Lemke-Howson algorithm and conduct a statistical analysis of its performance in solving bimatrix games of various sizes. We analyze the impacts of different input parameters on the solving time. We also compare the algorithm with more recent Lasserre hierarchies based on semidefinite programming.
We did not find statistical analyses of the performance of the Lemke-Howson algorithm in the literature, making this the primary contribution of this thesis.
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