Distributed load managers exhibit thrashing where tasks are repeatedly moved between locations due to incomplete global load information. This paper shows that systems of Autonomou...
Web systems suffer from an inability to satisfy heterogeneous needs of many users. A remedy for the negative effects of the traditional "one-size-fits-all'' approac...
BDI (Belief, Desire, Intention) agent systems are very powerful, but they lack the ability to incorporate planning. There has been some previous work to incorporate planning withi...
One of our goals when building the University of Michigan Digital Library UMDL has been to prototype an architecture that can continually recon gure itself as users, contents, and ...
Edmund H. Durfee, Tracy Mullen, Sunju Park, Jos&ea...
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...