This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
Marilyn A. Walker, Jeanne Frommer, Shrikanth Naray...
In the RETSINA multi-agent system, each agent is provided with an internal planning component—the RETSINA planner. Each agent, using its internal planner, formulates detailed pla...
Massimo Paolucci, Onn Shehory, Katia P. Sycara, Di...
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...
The recent and unprecedented surge of public interest in peer-to-peer file sharing has led to a variety of interesting research questions. In this paper, we will address the ince...
Philippe Golle, Kevin Leyton-Brown, Ilya Mironov, ...
System performance in multi-agent resource allocation systems can often improve if individual agents reduce their activity. Agents in such systems need a way to modulate their ind...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...