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JAIR
2002
120views more  JAIR 2002»
13 years 5 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling

Publication
273views
13 years 21 days ago
Monte Carlo Value Iteration for Continuous-State POMDPs
Partially observable Markov decision processes (POMDPs) have been successfully applied to various robot motion planning tasks under uncertainty. However, most existing POMDP algo...
Haoyu Bai, David Hsu, Wee Sun Lee, and Vien A. Ngo
CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 1 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
NIPS
2004
13 years 6 months ago
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
Pascal Poupart, Craig Boutilier
PAMI
2007
186views more  PAMI 2007»
13 years 5 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little