In this paper, a hybrid method known as evolving neural networks is used by No-Limit Texas Hold’em Poker playing agents to make betting decisions. Evolutionary algorithms and neural networks have been shown to find solutions in large and non-linear decision spaces and have proven to aid decision making in No-Limit Texas Hold’em Poker.
These simple features result in No-Limit Texas Hold’em Poker having a large decision space in comparison to other classic games such as Backgammon and Chess. Each player receives cards dealt randomly and does not know which cards his opponents have been dealt. No-Limit Texas Hold’em Poker is a stochastic game of imperfect information.
