The task of playing poker (Texas Hold’em) is a very difficult one. Unlike traditional games worked on in the field of Artificial Intelligence, in Poker we must deal with incomplete information. Games like Chess and Checkers are examples perfect information games, where the entire state of the game is known to all players. In Texas Hold’em, there can be anywhere from 2 to 10 players, and we have no idea what cards they may be holding. To complicate things, players may deliberately deceive you (by bluffing with a weak hand or slow playing a strong hand). I have been studying methods to do opponent modeling in poker. 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. This is no trivial task. Some of my more recent work in this area is shown below.