Real-time Opponent Modeling in Trick-taking Card Games
Jeffrey Long and Michael Buro
As adversarial environments become more complex, it is increasingly crucial for agents to exploit the mistakes of weaker opponents, particularly in the context of winning tournaments and competitions. In this work, we present a simple post processing technique, which we call Perfect Information Post-Mortem Analysis (PIPMA), that can quickly assess the playing strength of an opponent in certain classes of game environments. We apply this technique to skat, a popular german card game, and show that we can achieve substantial performance gains against not only players weaker than our program, but against stronger players as well. Most importantly, PIPMA can model the opponent after only a handful of games. To our knowledge, this makes our work the first successful example of an opponent modeling technique that can adapt its play to a particular opponent in real time in a complex game setting.