Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
Information retrieval which aims to provide people with easy access to all kinds of information is now becoming more and more emphasized. However, most approaches to information r...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Meeting timing constraint is one of the most important issues for modern design automation tools. This situation is exacerbated with the existence of process variation. Current hi...
Abstract. Motivated by the analogies to statistical physics, the deterministic annealing (DA) method has successfully been demonstrated in a variety of application. In this paper, ...