Abstract—Developing autonomous systems that patrol environments for detecting intruders is a topic of increasing relevance in security applications. An important aspect of these ...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Since real-time search provides an attractive framework for resource-bounded problem solving, this paper extends the framework for autonomous agents and for a multiagent world. To ...
We propose an enhanced mechanism for selecting partners for multi-attribute negotiation. The mechanism employs possibilistic case-based reasoning. The possibility of successful ne...
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...