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 ...
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...
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...
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...
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...