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128
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NIPS
2003
15 years 7 months ago
Approximate Policy Iteration with a Policy Language Bias
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...
Alan Fern, Sung Wook Yoon, Robert Givan
PKDD
2010
Springer
122views Data Mining» more  PKDD 2010»
15 years 4 months ago
Exploration in Relational Worlds
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...
Tobias Lang, Marc Toussaint, Kristian Kersting
VTC
2007
IEEE
16 years 2 days ago
Q-Learning-based Hybrid ARQ for High Speed Downlink Packet Access in UMTS
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...
Chung-Ju Chang, Chia-Yuan Chang, Fang-Ching Ren
154
Voted
IPTPS
2003
Springer
15 years 11 months ago
Adaptive Peer Selection
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...
AUTOMATICA
2006
101views more  AUTOMATICA 2006»
15 years 5 months ago
A risk-sensitive approach to total productive maintenance
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...
Abhijit Gosavi