Texas Hold'em Poker is similar to other poker variants in that our decision process is controlled by outside factors as much as the cards themselves. Factors such as our seating position, stack size, the stage of the tournament and prior bets can strongly influence a players decision to bet or fold on a given hand of cards. Previous research has explored the use of these factors as means of betting influence through use of a genetic algorithm applied in an evolutionary learning process. However in this previous work, the evolved player performed against scripted opponents at the table. In this paper we describe a co-evolutionary approach where all players on the table are part of the learning process. Results vary wildly between simulations, with further analysis showing that the ability to create robust strategies is difficult given the adversarial dynamic of the game. Despite this, agents are still capable of adhering to guidelines recommended in expert literature.
['Thomas Thompson', 'John Levine', 'Russell Wotherspoon']
Evolution of counter-strategies: Application of co-evolution to Texas Hold'em Poker