Constructing Symbolic Representations for High-Level Planning
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 s...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Association for the Advancement of Artificial Intelligence (AAAI)
2016
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| Online Access: | http://hdl.handle.net/1721.1/100720 https://orcid.org/0000-0002-8657-2450 https://orcid.org/0000-0001-6054-7145 |
| Summary: | 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. |
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