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» Multi-objective Model Checking of Markov Decision Processes
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JMLR
2006
116views more  JMLR 2006»
13 years 8 months ago
Point-Based Value Iteration for Continuous POMDPs
We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are ...
Josep M. Porta, Nikos A. Vlassis, Matthijs T. J. S...
CCE
2004
13 years 8 months ago
An algorithmic framework for improving heuristic solutions: Part II. A new version of the stochastic traveling salesman problem
The algorithmic framework developed for improving heuristic solutions of the new version of deterministic TSP [Choi et al., 2002] is extended to the stochastic case. To verify the...
Jaein Choi, Jay H. Lee, Matthew J. Realff
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 7 months ago
Variable resolution decomposition for robotic navigation under a POMDP framework
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Robert Kaplow, Amin Atrash, Joelle Pineau
IJRR
2010
162views more  IJRR 2010»
13 years 7 months ago
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
NIPS
2008
13 years 10 months ago
MDPs with Non-Deterministic Policies
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...
Mahdi Milani Fard, Joelle Pineau