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» Prob-Maxn: Playing N-Player Games with Opponent Models
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AAAI
2006
13 years 5 months ago
Prob-Maxn: Playing N-Player Games with Opponent Models
Much of the work on opponent modeling for game tree search has been unsuccessful. In two-player, zero-sum games, the gains from opponent modeling are often outweighed by the cost ...
Nathan R. Sturtevant, Martin Zinkevich, Michael H....
GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
13 years 10 months ago
Evolving explicit opponent models in game playing
Opponent models are necessary in games where the game state is only partially known to the player, since the player must infer the state of the game based on the opponent’s acti...
Alan J. Lockett, Charles L. Chen, Risto Miikkulain...
ATAL
2011
Springer
12 years 4 months ago
Game theory-based opponent modeling in large imperfect-information games
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
Sam Ganzfried, Tuomas Sandholm
CIG
2006
IEEE
13 years 10 months ago
Evolving Adaptive Play for the Game of Spoof Using Genetic Programming
Abstract— Many games require opponent modelling for optimal performance. The implicit learning and adaptive nature of evolutionary computation techniques offer a natural way to d...
Mark Wittkamp, Luigi Barone
GAMEON
2007
13 years 5 months ago
Opponent Modeling in Real-Time Strategy Games
Real-time strategy games present an environment in which game AI is expected to behave realistically. One feature of realistic behaviour in game AI is the ability to recognise the...
Frederik Schadd, Sander Bakkes, Pieter Spronck