This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
We consider a new model for computing with uncertainty. It is desired to compute a function fX1; : : : ; Xn where X1; : : : ; Xn are unknown, but guaranteed to lie in speci ed i...
Classical retrieval models support content-oriented searching for documents using a set of words as data model. However, in hypertext and database applications we want to consider...