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AIPS
2006
13 years 10 months ago
Stochastic Over-Subscription Planning Using Hierarchies of MDPs
Nicolas Meuleau, Ronen I. Brafman, Emmanuel Benaze...
AI
2000
Springer
13 years 8 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»
14 years 2 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 11 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 10 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