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» Coarticulation in Markov Decision Processes
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AIPS
2008
13 years 10 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
13 years 10 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-...
IJCAI
2007
13 years 9 months ago
A Fast Analytical Algorithm for Solving Markov Decision Processes with Real-Valued Resources
Agents often have to construct plans that obey deadlines or, more generally, resource limits for real-valued resources whose consumption can only be characterized by probability d...
Janusz Marecki, Sven Koenig, Milind Tambe
ICWS
2004
IEEE
13 years 9 months ago
Dynamic Workflow Composition using Markov Decision Processes
The advent of Web services has made automated workflow composition relevant to Web based applications. One technique that has received some attention, for automatically composing ...
Prashant Doshi, Richard Goodwin, Rama Akkiraju, Ku...
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng