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DCC
2005
IEEE
14 years 7 months ago
Asymptotics of the Entropy Rate for a Hidden Markov Process
We calculate the Shannon entropy rate of a binary Hidden Markov Process (HMP), of given transition rate and noise (emission), as a series expansion in . The first two orders are ca...
Or Zuk, Ido Kanter, Eytan Domany
CDC
2009
IEEE
133views Control Systems» more  CDC 2009»
14 years 7 days ago
Arbitrarily modulated Markov decision processes
— We consider decision-making problems in Markov decision processes where both the rewards and the transition probabilities vary in an arbitrary (e.g., nonstationary) fashion. We...
Jia Yuan Yu, Shie Mannor
AIPS
2009
13 years 8 months ago
Minimal Sufficient Explanations for Factored Markov Decision Processes
Explaining policies of Markov Decision Processes (MDPs) is complicated due to their probabilistic and sequential nature. We present a technique to explain policies for factored MD...
Omar Zia Khan, Pascal Poupart, James P. Black
COLING
2010
13 years 2 months ago
Controlling Listening-oriented Dialogue using Partially Observable Markov Decision Processes
This paper investigates how to automatically create a dialogue control component of a listening agent to reduce the current high cost of manually creating such components. We coll...
Toyomi Meguro, Ryuichiro Higashinaka, Yasuhiro Min...
IJCAI
2007
13 years 9 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup