在Python纳什均衡 [英] Nash equilibrium in Python

问题描述

有一个Python库，在那里，解决了两个人的零游戏纳什均衡？我知道该溶液可以以线性约束条件可以记录下来，并在理论上SciPy的应该能够优化它。然而，对于二人零游戏的溶液是精确的并且唯一的，但是一些解算器无法收敛为一定的问题。

Is there a Python library out there that solves for the Nash equilibrium of two-person zero-games? I know the solution can be written down in terms of linear constraints and, in theory, scipy should be able to optimize it. However, for two-person zero-games the solution is exact and unique, but some of the solvers fail to converge for certain problems.

而不是列出所有的Python的网站上线性规划的库，我想知道是什么库是最有效的在易用性和速度方面

Rather than listing any of the libraries on Linear programing on the Python website, I would like to know what library would be most effective in terms of ease of use and speed.

推荐答案

雷蒙德的Hettinger写的配方解决零和收益矩阵。它应该成为你的目的没有问题。

Raymond Hettinger wrote a recipe for solving zero-sum payoff matrices. It should serve your purposes alright.

作为解决博弈论一个更一般的图书馆，还有专为设计什么。但是，像你说的，SciPy的可以解决这样的优化问题。你也许可以做一些与 GarlicSim ，号称是任何一种模拟：物理学，博弈论......但我从来没有使用过它之前，所以我不能建议

As for a more general library for solving game theory, there's nothing specifically designed for that. But, like you said, scipy can tackle optimization problems like this. You might be able to do something with GarlicSim, which claims to be for "any kind of simulation: Physics, game theory..." but I've never used it before so I can't recommend it.

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