numpy tensorflow phevaluator ++?
open main and run the program
you can change the parameters in the config file, however make sure NN are trained with new parameters in mind
Creates the players, sets up the game, and controls the current players and flow of the game, together with deciding what legal actions a player can take
Creates the decks, picking cards based on current cards on table, computes win probability using rollout which is used to compute the cheat sheet(which is not beeing used). Also more importantly it can rank any two collections of hands, currently using an extension phyevaluator, because my own was too slow. It uses this to create the utility matrix used in resolving.
creates and modifies states based on legal actions from the game manager and selection of the players or other components that need to change the states.
takes a state and generates a tree of nodes with different states, which is used to update ranges and evaluations that generates regret matrixes which is used to optimalize strategies. This is used for resolving and by the resolving AI agents.
generates training data using the resolver. It bootstraps training where the utility matrixes are used to train generate the river data, and then the river model is used for the turn data etc...
go to the NN_creation file and run the program. Make sure lower tier models are created before creating the data. The sequence is (flop-turn-river) (data generation takes a long time so the current models have only about 100 instances, however training data can be accumulated over time, simply generate more data and then a new model)