In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
Communication among agents requires a common vocabulary to facilitate successful information exchange. One way to achieve this is to assume the existence of a common ontology amon...
Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such inter...
This paper addresses the problem of plan recognition for multiagent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. T...
Software maintenance is responsible for as much as two thirds of the cost of any software, and is consequently an important research area. In this paper we focus on the change pro...