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» A Markov Reward Model Checker
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ICML
2008
IEEE
14 years 7 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
ICAC
2008
IEEE
14 years 1 months ago
Digital Evolution of Behavioral Models for Autonomic Systems
We describe an automated method to generating models of an autonomic system. Specifically, we generate UML state diagrams for a set of interacting objects, including the extensio...
Heather Goldsby, Betty H. C. Cheng, Philip K. McKi...
JMLR
2010
135views more  JMLR 2010»
13 years 1 months ago
Finite-sample Analysis of Bellman Residual Minimization
We consider the Bellman residual minimization approach for solving discounted Markov decision problems, where we assume that a generative model of the dynamics and rewards is avai...
Odalric-Ambrym Maillard, Rémi Munos, Alessa...
QEST
2008
IEEE
14 years 1 months ago
Symbolic Magnifying Lens Abstraction in Markov Decision Processes
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
14 years 1 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...