![]() This simulation package contains the Poker AI (Pokibot, Sparbot, Vexbot)ĭeveloped at the University of Alberta. One of the best resources for the poker coder is the poker simulation Some of my more recent work in this area is shown below. In this case, we are interested in being able to accurately guess what cards a player may be holding and how he may play them. I have been studying methods to do opponent modeling in poker. To complicate things, players may deliberately deceive you (by bluffing with a weak hand or slow playing a strong hand). In Texas Hold'em, there can be anywhere from 2 to 10 players, and we have no idea what cards they may be holding. Games like Chess and Checkers are examples perfect information games, where the entire state of the game is known to all players. Unlike traditional games worked on in the field of Artificial Intelligence, in Poker we must deal with incomplete information. The task of playing poker (Texas Hold'em) is a very difficult one. I joined the group in 1999 and completed my MSc. Anyone considering working on Poker AI should get familiar with the work done here. They have published many papers over those years with detailed algorithms and results. The University of Alberta Computer Poker Research Group has been researching Artificial Intelligence applied to Poker since the mid-90's. ![]() University of Alberta Computer Poker Research Group
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