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AIPS
2006
13 years 6 months ago
Stochastic Over-Subscription Planning Using Hierarchies of MDPs
Nicolas Meuleau, Ronen I. Brafman, Emmanuel Benaze...
AI
2000
Springer
13 years 4 months ago
Stochastic dynamic programming with factored representations
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Craig Boutilier, Richard Dearden, Moisés Go...
ICRA
2006
IEEE
134views Robotics» more  ICRA 2006»
13 years 10 months ago
Hierarchical Map Building and Planning based on Graph Partitioning
— Mobile robot localization and navigation requires a map - the robot’s internal representation of the environment. A common problem is that path planning becomes very ineffic...
Zoran Zivkovic, Bram Bakker, Ben J. A. Kröse
AIPS
2010
13 years 7 months ago
When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
Emma Brunskill
AAAI
2010
13 years 6 months ago
Relational Partially Observable MDPs
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Chenggang Wang, Roni Khardon