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» Approximating Markov Processes by Averaging
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DCC
2004
IEEE
14 years 7 months ago
On the Entropy of a Hidden Markov Process
We study the entropy rate of a hidden Markov process (HMP) defined by observing the output of a binary symmetric channel whose input is a first-order binary Markov process. Despit...
Philippe Jacquet, Gadiel Seroussi, Wojciech Szpank...
AAAI
2004
13 years 8 months ago
Solving Generalized Semi-Markov Decision Processes Using Continuous Phase-Type Distributions
We introduce the generalized semi-Markov decision process (GSMDP) as an extension of continuous-time MDPs and semi-Markov decision processes (SMDPs) for modeling stochastic decisi...
Håkan L. S. Younes, Reid G. Simmons
ICRA
2007
IEEE
154views Robotics» more  ICRA 2007»
14 years 1 months ago
Oracular Partially Observable Markov Decision Processes: A Very Special Case
— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
Nicholas Armstrong-Crews, Manuela M. Veloso
CORR
2011
Springer
183views Education» more  CORR 2011»
13 years 2 months ago
Mean-Variance Optimization in Markov Decision Processes
We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomiz...
Shie Mannor, John N. Tsitsiklis
ICML
2005
IEEE
14 years 8 months ago
Coarticulation: an approach for generating concurrent plans in Markov decision processes
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
Khashayar Rohanimanesh, Sridhar Mahadevan