Multi-agent decision problems, in which independent agents have to agree on a joint plan of action or allocation of resources, are central to AI. In such situations, agents' ...
Reshef Meir, Maria Polukarov, Jeffrey S. Rosensche...
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
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...
This paper describes the results of applying a modified version of hierarchical task-network (HTN) planning to the problem of declarer play in contract bridge. We represent inform...
Stephen J. J. Smith, Dana S. Nau, Thomas A. Throop
We present an experimental investigation of the performance of the Lemke-Howson algorithm, which is the most widely used algorithm for the computation of a Nash equilibrium for bi...