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» Coarticulation in Markov Decision Processes
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ICML
2006
IEEE
14 years 8 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
ATAL
2009
Springer
14 years 2 months ago
Solving multiagent assignment Markov decision processes
We consider the setting of multiple collaborative agents trying to complete a set of tasks as assigned by a centralized controller. We propose a scalable method called“Assignmen...
Scott Proper, Prasad Tadepalli
LICS
2007
IEEE
14 years 1 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
22
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STACS
2007
Springer
14 years 1 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
13 years 11 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