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» Incorporating Opponent Models into Adversary Search
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AAAI
1996
13 years 5 months ago
Incorporating Opponent Models into Adversary Search
This work presents a generalized theoretical framework that allows incorporation of opponent models into adversary search. We present the M algorithm, a generalization of minimax ...
David Carmel, Shaul Markovitch
AI
1998
Springer
13 years 3 months ago
Pruning Algorithms for Multi-Model Adversary Search
The Multi-model search framework generalizes minimax to allow exploitation of recursive opponent models. In this work we consider adding pruning to the multi-model search. We prov...
David Carmel, Shaul Markovitch
ECAI
2004
Springer
13 years 9 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...
AAMAS
2005
Springer
13 years 3 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger
ATAL
2007
Springer
13 years 9 months ago
An adversarial environment model for bounded rational agents in zero-sum interactions
Multiagent environments are often not cooperative nor collaborative; in many cases, agents have conflicting interests, leading to adversarial interactions. This paper presents a ...
Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschei...