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AI Magazine

AI Game-Playing Techniques: Are They Useful for Anything Other Than Games? In conjunction with the American Association for Artificial Intelligence's Hall of Champions exhibit, the Innovative Applications of Artificial Intelligence held a panel discussion entitled "AI Game-Playing Techniques: Are They Useful for Anything Other Than Games?" This article summarizes the panelists' comments about whether ideas and techniques from AI game playing are useful elsewhere and what kinds of game might be suitable as "challenge problems" for future research. AAAI-98's Hall of Champions exhibit) is an AI games researcher at the University of Alberta and author of the checkers program The early research on the alpha-beta search algorithm was useful in establishing a foundation for AI theories of heuristic search, and these theories have been useful in many areas of AI. Several of the panelists (particularly Schaeffer, Wilkins, and Fotland) pointed out that the minimax search algorithms traditionally associated with AI have only a limited range of applicability.


A Gamut of Games

AI Magazine

In 1950, Claude Shannon published his seminal work on how to program a computer to play chess. Since then, developing game-playing programs that can compete with (and even exceed) the abilities of the human world champions has been a long-sought-after goal of the AI research community. In Shannon's time, it would have seemed unlikely that only a scant 50 years would be needed to develop programs that play world-class backgammon, checkers, chess, Othello, and Scrabble. These remarkable achievements are the result of a better understanding of the problems being solved, major algorithmic insights, and tremendous advances in hardware technology. Computer games research is one of the important success stories of AI.


A Gamut of Games

AI Magazine

In 1950, Claude Shannon published his seminal work on how to program a computer to play chess. Since then, developing game-playing programs that can compete with (and even exceed) the abilities of the human world champions has been a long-sought-after goal of the AI research community. In Shannon's time, it would have seemed unlikely that only a scant 50 years would be needed to develop programs that play world-class backgammon, checkers, chess, Othello, and Scrabble. These remarkable achievements are the result of a better understanding of the problems being solved, major algorithmic insights, and tremendous advances in hardware technology. Computer games research is one of the important success stories of AI. This article reviews the past successes, current projects, and future research directions for AI using computer games as a research test bed.


A Re-Examination of Brute-Force Search

AAAI Conferences

In August 1992, the World Checkers Champion, Dr. Marion Tinsley, defended his title against the computer program Chinook. The best-of-40-game match was won by Tinsley with 4 wins to the program's 2. This was the first time in history that a program played for a human World Championship. Chinook, with its deep search and endgame databases, has established itself as a Grandmaster checker player. However, the match demonstrated that current brute-force game-playing techniques alone will be insufficient to defeat human champions in games as complex as checkers. This paper reexamines brute-force search and uses anecdotal evidence to argue that there comes a point where additional search is not cost effective. This limit, which we believe we are close to in checkers, becomes an obstacle to further progress. The problems of deep brute-force search described in this paper must be addressed before computers will be dominant in games such as checkers and chess.


AI Game-Playing Techniques

AI Magazine

In conjunction with the Association for the Advancement of Artificial Intelligence's Hall of Champions exhibit, the Innovative Applications of Artificial Intelligence held a panel discussion entitled "AI Game-Playing Techniques: Are They Useful for Anything Other Than Games?" This article summarizes the panelists' comments about whether ideas and techniques from AI game playing are useful elsewhere and what kinds of game might be suitable as "challenge problems" for future research.