RADAR is a multiagent system with a mixed-initiative user interface designed to help office workers cope with email overload. RADAR agents observe experts to learn models of their...
Aaron Steinfeld, Andrew Faulring, Asim Smailagic, ...
There has been a growing interest in designing multi-agent based interactive dramas. A key research challenge faced in the design of these systems is to support open-ended user in...
Security at major locations of economic or political importance is a key concern around the world, particularly given the threat of terrorism. Limited security resources prevent f...
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
In this paper, I will discuss a set of techniques for supporting limited variable binding in behavior-based systems. This adds additional useful expressivity while preserving the ...