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COLT
2007
Springer
13 years 11 months ago
Bounded Parameter Markov Decision Processes with Average Reward Criterion
Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, t...
Ambuj Tewari, Peter L. Bartlett
ECML
2004
Springer
13 years 11 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
CORR
2006
Springer
140views Education» more  CORR 2006»
13 years 5 months ago
Nearly optimal exploration-exploitation decision thresholds
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. Optimal decision thresholds ...
Christos Dimitrakakis
ICML
1999
IEEE
14 years 6 months ago
Using Reinforcement Learning to Spider the Web Efficiently
Consider the task of exploring the Web in order to find pages of a particular kind or on a particular topic. This task arises in the construction of search engines and Web knowled...
Jason Rennie, Andrew McCallum
BROADNETS
2004
IEEE
13 years 9 months ago
Efficient QoS Provisioning for Adaptive Multimedia in Mobile Communication Networks by Reinforcement Learning
The scarcity and large fluctuations of link bandwidth in wireless networks have motivated the development of adaptive multimedia services in mobile communication networks, where i...
Fei Yu, Vincent W. S. Wong, Victor C. M. Leung