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» Percentile Optimization for Markov Decision Processes with P...
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54
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IOR
2010
64views more  IOR 2010»
14 years 8 months ago
Percentile Optimization for Markov Decision Processes with Parameter Uncertainty
Erick Delage, Shie Mannor
72
Voted
ICML
2007
IEEE
15 years 11 months ago
Percentile optimization in uncertain Markov decision processes with application to efficient exploration
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...
Erick Delage, Shie Mannor
99
Voted
COLT
2007
Springer
15 years 4 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
78
Voted
ECML
2005
Springer
15 years 3 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
84
Voted
AIPS
2008
15 years 18 days ago
Bounded-Parameter Partially Observable Markov Decision Processes
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...
Yaodong Ni, Zhi-Qiang Liu