2007 AAAI Computer Poker Competition: "The 2007 poker competition consisted of 15 competitors from 7 countries and 43 bots. Matches were played on 32 machines running for a month, playing over 17 million hands of poker. The results were announced at AAAI 2007 on July 24, 2007 in Vancouver BC."

• See this related article: Claremont man's BluffBot beats colleges' efforts. By Will Bigham. San Bernardino County Sun (September 4, 2007). "A poker-playing robot co-developed by lifelong Claremont resident Jay Cordes overwhelmed its opponents and took first prize at a recent robot poker competition in Vancouver, British Columbia. The robot, called BluffBot 2.0, went undefeated in matches against its nine opponents, which included bots developed by teams at top research institutions such as Carnegie Mellon University, University of Minnesota and University of Alberta. The robot was created by software developer Teppo Salonen and developed by both Salonen and Cordes in their spare time. ... BluffBot is not yet advanced enough to consistently beat experienced poker players, said Cordes, a software developer at Prestige Software, but the developers hope to some day create a program that will. ... After being blindsided by BluffBot at this year's competition, which was sponsored by the Association for the Advancement of Artificial Intelligence, [Michael] Bowling and other researchers hope to learn from their defeat and develop a superior bot. 'A lot of the universities are wondering, "What did they do, and how can we learn from it?"' Bowling said. 'And we don't know the answers to that.' A free version of BluffBot 1.0 can be downloaded at www.bluffbot.com."

The First AAAI Computer Poker Competition: July 16-20, 2006 at the Twenty-First National Conference on Artificial Intelligence (AAAI-06) in Boston, MA. "The game will be heads-up limit Texas Hold-Em. In order to encourage participation, attendance is appreciated but not required, there will be no registration fee, and no prize but victory."

• Articles about the competition can be found in our July 2006 AI in the news archive and the General Index to AI in the news: Games & Puzzles.

Computers and Poker? You Bet. Podcast (July 26, 2005). "[Jonathan Erickson of] Dr. Dobb's Journal discusses the high-stakes world of computers and Poker with Jonathan Schaeffer, leader of the University of Alberta's Computer Poker Research Group. Computers are getting better, but are they up to taking the best human players to the bank on a regular basis?"

• Visit the University of Alberta Computer Poker Research Group

Windows, lose, draw - Alberta researchers develop a computer program that knows when you're bluffing. By Charlie Gillis. National Post (July 27, 2002). "This week, Mr. [Darse] Billings and a team of University of Alberta researchers are publicizing a poker-playing computer program that does what many a putative gambler cannot -- it successfully processes the mercurial and misleading information it receives in the heat of a game. The system represents a significant stride in artificial intelligence because it effectively guesses whether an opponent is bluffing, wavering or playing his hands arrow-straight. By doing so, it goes beyond programs developed for games such as chess and backgammon, which sift through finite sets of moves before choosing a course."

The University of Alberta Computer Poker Research Group. "Poker is an excellent domain for artificial intelligence research. It offers many new challenges since it is a game of imperfect information, where decisions must be made under conditions of uncertainty. Multiple competing agents must deal with probabilistic knowledge, risk management, deception, and opponent modeling, among other things. One of the products of our research is the implementation of a poker playing program named Poki."

• Don't miss their list of publications and articles, as well as the links to related sites and other researchers, and be sure to listen to this podcast about their research.

The challenge of poker. By Darse Billings , Aaron Davidson, Jonathan Schaeffer, and Duane Szafron In Artificial Intelligence, January 2002 (Volume: 134, Issue: 1-2). "This paper describes the design considerations and architecture of the poker program Poki. In addition to methods for hand evaluation and betting strategy, Poki uses learning techniques to construct statistical models of each opponent, and dynamically adapts to exploit observed patterns and tendencies. The result is a program capable of playing reasonably strong poker, but there remains considerable research to be done to play at world-class level." - from the Abstract.

Poker as a Testbed for Machine Intelligence Research. By Darse Billings, Denis Papp, Jonathan Schaeffer, Duane Szafron; Department of Computing Science, University of Alberta (1998). Be sure to see Table 1: Characteristics of AI problems and how they are exhibited by poker.

Computers, Games and the Real World. By Matthew L. Ginsberg. Scientific American (special issue: Exploring Intelligence - Winter 1998). "More than just competing with people, game-playing machines complement human thinking by offering alternative methods to solving problems."

Generating and Solving Imperfect Information Games. By Daphne Koller and Avi Pfeffer. (1995) "Work on game playing in AI has typically ignored games of imperfect information such as poker. In this paper, we present a framework for dealing with such games."

Playing Your Cards Right - Poker comes out of the back room and into the computer science lab. By Ivars Peterson. Science News (July 18, 1998). "Poker is an example of a game of incomplete information in which chance plays a role. Whereas a chess player sees the disposition of all the pieces all the time, a poker player sees only some of the cards -- drawn or dealt from a shuffled deck -- that are in play."

Poker Academy. Be sure to see thier page about Artificial Intelligence.

Related AI Topics Pages

• Bridge
• Checkers
• Chess
• Crossword Puzzles
• Game Theory (@ Multi-Agent Systems)
• Go
• More Games & Puzzles
• Othello
• Overview
• Scrabble
• Traveling Salesperson & NP-Complete Problems