In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Aircraft maintenance is performed by mechanics who are required, by regulation, to consult expert engineers for repair instructions and approval. In addition to their own experien...
Onn Shehory, Katia P. Sycara, Gita Sukthankar, Vic...
We discuss the design of a class of agents that we call adaptive web site agents. The goal of such an agent is to help a user find information at a particular web site, adapting i...
For a dynamic, evolving multiagent auction, we have developed an adaptive agent bidding strategy (called the p-strategy) based on stochastic modeling. The p-strategy takes into ac...
Sunju Park, Edmund H. Durfee, William P. Birmingha...
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. E ective agent interactions in such domains raise some of most fundamental research...
Intelligent environmentsareaninterestingdevelopmentandresearchapplication problem for multi-agent systems.The functionalandspatialdistribution of tasksnaturally lendsitself to a m...
Victor R. Lesser, Michael Atighetchi, Brett Benyo,...