Constructing Symbolic Representations for High-Level Planning
Author(s)Konidaris, George D.; Kaelbling, Leslie P.; Lozano-Perez, Tomas
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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.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 28th AAAI Conference on Artificial Intelligence
Association for the Advancement of Artificial Intelligence (AAAI)
Konidaris, George, Leslie Pack Kaelbling, and Tomas Lozano-Perez. "Constructing Symbolic Representations for High-Level Planning." 28th AAAI Conference on Artificial Intelligence (July 2014).
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