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AIIDE
2009
9 years 3 months ago
Improving Offensive Performance Through Opponent Modeling
Although in theory opponent modeling can be useful in any adversarial domain, in practice it is both difficult to do accurately and to use effectively to improve game play. In thi...
Kennard Laviers, Gita Sukthankar, David W. Aha, Ma...
MLMTA
2003
9 years 3 months ago
Using a Two-Layered Case-Based Reasoning for Prediction in Soccer Coach
Abstract— The prediction of the future states in MultiAgent Systems has been a challenging problem since the begining of MAS. Robotic soccer is a MAS environment in which the pre...
Mazda Ahmadi, Abolfazl Keighobadi Lamjiri, Mayssam...
AAAI
2006
9 years 4 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....
GAMEON
2007
9 years 4 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
IDEAL
2009
Springer
9 years 7 months ago
The Winning Advantage: Using Opponent Models in Robot Soccer
Opponent modeling is a skill in multi-agent systems (MAS) which attempts to create a model of the behavior of the opponent. This model can be used to predict the future actions of ...
José Antonio Iglesias, Juan Antonio Fern&aa...
GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
9 years 8 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
2009
Springer
9 years 9 months ago
Facing the challenge of human-agent negotiations via effective general opponent modeling
Automated negotiation agents capable of negotiating efficiently with people must deal with the fact that people are diverse in their behavior and each individual might negotiate ...
Yinon Oshrat, Raz Lin, Sarit Kraus
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