Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
We present a combinatorial framework for the study of a natural class of distributed optimization problems that involve decisionmaking by a collection of n distributed agents in th...
This paper discusses conditions under which some of the “higher level” mental concepts applicable to human beings might also be applicable to artificial agents. The key idea ...
A dynamic model of a multiagent system defines a probability distribution over possible system behaviors over time. Alternative representations for such models present tradeoffs i...
Quang Duong, Michael P. Wellman, Satinder P. Singh...
Bayesian games can be used to model single-shot decision problems in which agents only possess incomplete information about other agents, and hence are important for multiagent co...
Frans A. Oliehoek, Matthijs T. J. Spaan, Jilles St...