We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
Abstract. One of the key problems in model-based reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large relational domains, in wh...
Abstract-In this paper, a Q-learning-based hybrid automatic repeat request (Q-HARQ) scheme is proposed to achieve efficient resource utilization for high speed downlink packet acc...
In a peer-to-peer file-sharing system, a client desiring a particular file must choose a source from which to download. The problem of selecting a good data source is difficult...
Daniel S. Bernstein, Zhengzhu Feng, Brian Neil Lev...
While risk-sensitive (RS) approaches for designing plans of total productive maintenance are critical in manufacturing systems, there is little in the literature by way of theoret...