Abstract
The article compares the performance and reliability of different methods for finding Nash equilibrium situations in antagonistic and bimatrix games. The NashPy library is used, which implements a convenient interface for searching for equilibrium situations. All methods are implemented in pure Python language. The comparison showed that the support_enumeration method finds all equilibrium situations, but its running time grows exponentially. Therefore, when the dimension is greater than 15, it is recommended to use the vertex_enumeration method, which also finds all equilibrium situations, but does it faster. If you need to find any one equilibrium, it is better to use the lemke_howson_enumeration method, which works very quickly, but returns only one solution. The article clearly presents graphs of the time spent searching for equilibrium depending on the dimension of the problem.
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