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LICS
2007
IEEE
15 years 6 months ago
Limits of Multi-Discounted Markov Decision Processes
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. The payoff received by the controller can be evaluated in different ways, dep...
Hugo Gimbert, Wieslaw Zielonka
STACS
2007
Springer
15 years 6 months ago
Pure Stationary Optimal Strategies in Markov Decision Processes
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. Performances of an MDP are evaluated by a payoff function. The controller of ...
Hugo Gimbert
ICTAI
2000
IEEE
15 years 3 months ago
Building efficient partial plans using Markov decision processes
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
Pierre Laroche
AIPS
2008
15 years 2 months 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
FLAIRS
2008
15 years 2 months ago
A Novel Prioritization Technique for Solving Markov Decision Processes
We address the problem of computing an optimal value function for Markov decision processes. Since finding this function quickly and accurately requires substantial computation ef...
Jilles Steeve Dibangoye, Brahim Chaib-draa, Abdel-...