Opponent Modeling in Poker

Poker is an interesting test-bed for artificial intelligence research. It is a game of imperfect knowledge, where multiple competing agents must deal with risk management, agent modeling, unreliable information and deception, much like decision-making applications in the real world. Agent modeling is one of the most difficult problems in decision-making applications and in poker it is essential to achieving high performance. This paper describes and evaluates Loki, a poker program capable of observing its opponents, constructing opponent models and dynamically adapting its play to best exploit patterns in the opponents' play.

• Type: Conference
• Year: 1998
• Where: AAAI
• Authors: Darse Billings, Denis Papp, Jonathan Schaeffer, Duane Szafron
• Keywords: AAAI 1998, Agent Modeling, Decision-making Applications, Intelligent Agents, Multiple Competing Agents