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» Planning in Factored Action Spaces with Symbolic Dynamic Pro...
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AIPS
1998
13 years 6 months ago
Solving Stochastic Planning Problems with Large State and Action Spaces
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Thomas Dean, Robert Givan, Kee-Eung Kim
UAI
2004
13 years 6 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
AI
2000
Springer
13 years 5 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...
AIPS
2008
13 years 7 months ago
Exact Dynamic Programming for Decentralized POMDPs with Lossless Policy Compression
High dimensionality of belief space in DEC-POMDPs is one of the major causes that makes the optimal joint policy computation intractable. The belief state for a given agent is a p...
Abdeslam Boularias, Brahim Chaib-draa
AIPS
2007
13 years 7 months ago
Approximate Solution Techniques for Factored First-Order MDPs
Most traditional approaches to probabilistic planning in relationally specified MDPs rely on grounding the problem w.r.t. specific domain instantiations, thereby incurring a com...
Scott Sanner, Craig Boutilier