Q:

Neural network package for strategy and games

I would like to use neural network method for approximating Nash Equilibrium for general games (especially card games)... What would be some standard package I could use? Thank you.

A:

It sounds like you should be looking into Gambit which is a GNU licensed package for exactly that sort of thing:

Open Source - GNU GPL Licence
Cross Platform Windows, Mac & Linux
GUI for exploring strategies & outcomes
Python API for implementing complex games, etc.
Command-line tools

gambit-enumpure: Enumerate pure-strategy equilibria of a game
gambit-enumpoly: Compute equilibria of a game using polynomial systems of equations
gambit-enummixed: Enumerate equilibria in a two-player game
gambit-gnm: Compute Nash equilibria in a strategic game using a global Newton method
gambit-ipa: Compute Nash equilibria in a strategic game using iterated polymatrix approximation
gambit-lcp: Compute equilibria in a two-player game via linear complementarity
gambit-lp: Compute equilibria in a two-player constant-sum game via linear programming
gambit-liap: Compute Nash equilibria using function minimization
gambit-simpdiv: Compute equilibria via simplicial subdivision
gambit-logit: Compute quantal response equilbria
gambit-convert: Convert games among various representations

