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CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 2 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
RECOMB
2003
Springer
16 years 4 months ago
Combining phylogenetic and hidden Markov models in biosequence analysis
A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...
Adam C. Siepel, David Haussler
GLOBECOM
2007
IEEE
15 years 7 months ago
Bursty Traffic in Energy-Constrained Opportunistic Spectrum Access
We design opportunistic spectrum access strategies for improving spectrum efficiency. In each slot, a secondary user chooses a subset of channels to sense and decides whether to ac...
Yunxia Chen, Qing Zhao, Ananthram Swami
AIPS
2000
15 years 5 months ago
Representations of Decision-Theoretic Planning Tasks
Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
Sven Koenig, Yaxin Liu
111
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AAAI
2010
15 years 5 months ago
Representation Discovery in Sequential Decision Making
Automatically constructing novel representations of tasks from analysis of state spaces is a longstanding fundamental challenge in AI. I review recent progress on this problem for...
Sridhar Mahadevan