Algorithms
Logic behind Neo AIs employs different combinations of neural networks, regret minimization and gradient search equilibrium approximation, decision trees, recursive search methods as well as expert algorithms from professional players in different poker games. Neural networks learning for opponent modeling is based on database with millions hand histories of real poker players. Neo analyzes accumulated statistical data which allows the AI to adjust its style of play against opponents. It’s important to note that Neo Poker Bots play fairly which means that AI knows neither your hole cards nor what cards are to be dealt for decision making and opponent modeling.
Performance
Neo Poker Bot is tested against real poker players and demonstrates excellent results over great number of hands. Neo was awarded at 2012 Annual Computer Poker Competition. For more information please visit competition official website.
Team
Neo Poker Laboratory successfully develops poker robots since 2004. Our top rated experts in math with unique skills and experience along with professional poker players constantly work to improve the quality of the AI.