In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
We present an approach to the bid-evaluation problem in a system for multi-agent contract negotiation, called MAGNET. The MAGNET market infrastructure provides support for a variet...
Erik S. Steinmetz, John Collins, Scott Jamison, Ra...
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
This paper explores the complications encountered when attempting to create a secure pervasive computing environment. The model introduced in this paper is primarily conceptual. T...
We present a theory of a modeler's problem decomposition skills in the context of optimal reasonzng -- the use of qualitative modeling to strategically guide numerical explor...