Constructing Symbolic Representations for High-Level Planning
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Kaebling_Constructing symbolic.pdf
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305.02 KB
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Author(s)
Konidaris, George D.
Kaelbling, Leslie P.
Lozano-Perez, Tomas
Date Issued
July 2014
Journal
Proceedings of the 28th AAAI Conference on Artificial Intelligence
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Citation
Konidaris, George, Leslie Pack Kaelbling, and Tomas Lozano-Perez. "Constructing Symbolic Representations for High-Level Planning." 28th AAAI Conference on Artificial Intelligence (July 2014).
Version
Author's final manuscript
Abstract
We consider the problem of constructing a symbolic description of a continuous, low-level environment for use in planning. We show that symbols that can represent the preconditions and effects of an agent's actions are both necessary and sufficient for high-level planning. This eliminates the symbol design problem when a representation must be constructed in advance, and in principle enables an agent to autonomously learn its own symbolic representations. The resulting representation can be converted into PDDL, a canonical high-level planning representation that enables very fast planning.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
http://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/view/8424
