Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
Autonomous systems operating in real-world environments must plan, schedule, and execute missions while robustly adapting to uncertainty and disturbance. One way to mitigate the e...
Representing and reasoning with an agent's preferences is important in many applications of constraints formalisms. Such preferences are often only partially ordered. One clas...
(Appears as a regular paper in the proceedings of IEEE International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, Washington D.C, Nov. 2002, p...
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...