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» Prob-Maxn: Playing N-Player Games with Opponent Models
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AAAI
1998
13 years 6 months ago
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 m...
Darse Billings, Denis Papp, Jonathan Schaeffer, Du...
JDCTA
2010
160views more  JDCTA 2010»
13 years 1 days ago
Learning and Decision Making in Human During a Game of Matching Pennies
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...
Jianfeng Hu, Xiaofeng Li, Jinghai Yin
AAAI
2000
13 years 6 months ago
Defining and Using Ideal Teammate and Opponent Agent Models
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
Peter Stone, Patrick Riley, Manuela M. Veloso
ATAL
2010
Springer
13 years 6 months ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings
ECAI
2004
Springer
13 years 10 months ago
Adversarial Constraint Satisfaction by Game-Tree Search
Many decision problems can be modelled as adversarial constraint satisfaction, which allows us to integrate methods from AI game playing. In particular, by using the idea of oppone...
Kenneth N. Brown, James Little, Páidí...