DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes
This paper presents an algorithm for finding approximately optimal policies in very large Markov decision processes by constructing a hierarchical model and then solving it approximately. It exploits factored representations to achieve compactness and efficiency and to discover connectivity properti...
Main Authors: | Barry, Jennifer (Contributor), Kaelbling, Leslie P. (Contributor), Lozano-Perez, Tomas (Contributor) |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
AAAI Press/International Joint Conferences on Artificial Intelligence,
2014-10-10T17:43:26Z.
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Subjects: | |
Online Access: | Get fulltext |
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