Multi-agent decision problems, in which independent agents have to agree on a joint plan of action or allocation of resources, are central to AI. In such situations, agents' ...
Reshef Meir, Maria Polukarov, Jeffrey S. Rosensche...
Reactive planning using assumptions is a well-known approach to tackle complex planning problems for nondeterministic, partially observable domains. However, assumptions may be wr...
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
In this paper we present the Behaviosite Paradigm, a new approach to coordination and control of distributed agents in a multiagent system, inspired by biological parasites with b...
Amit Shabtay, Zinovi Rabinovich, Jeffrey S. Rosens...