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CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 3 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
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
CDC
2010
IEEE
141views Control Systems» more  CDC 2010»
13 years 2 months ago
A dynamic programming algorithm for decentralized Markov decision processes with a broadcast structure
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast informati...
Jeff Wu, Sanjay Lall
CORR
2011
Springer
183views Education» more  CORR 2011»
13 years 2 months ago
Mean-Variance Optimization in Markov Decision Processes
We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomiz...
Shie Mannor, John N. Tsitsiklis
CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 7 months ago
Mean field for Markov Decision Processes: from Discrete to Continuous Optimization
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Nicolas Gast, Bruno Gaujal, Jean-Yves Le Boudec