Expressivity of Planning with Horn Description Logic Ontologies
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
State constraints in AI Planning globally restrict the legal environment states. Standard planning languages make closed-domain and closed-world assumptions. Here we address open-world state constraints formalized by planning over a description logic (DL) ontology. Previously, this combination of DL and planning has been investigated for the light-weight DL DL-Lite. Here we propose a novel compilation scheme into standard PDDL with derived predicates, which applies to more expressive DLs and is based on the rewritability of DL queries into Datalog with stratified negation. We also provide a new rewritability result for the DL Horn-ALCHOIQ, which allows us to apply our compilation scheme to quite expressive ontologies. In contrast, we show that in the slight extension Horn-SROIQ no such compilation is possible unless the weak exponential hierarchy collapses. Finally, we show that our approach can outperform previous work on existing benchmarks for planning with DL ontologies, and is feasible on new benchmarks taking advantage of more expressive ontologies.
Details
Original language | English |
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Title of host publication | Proceedings of the 36th AAAI Conference on Artificial Intelligence |
Pages | 5503-5511 |
Number of pages | 9 |
ISBN (electronic) | 978-1-57735-876-3 |
Publication status | Published - 2022 |
Peer-reviewed | Yes |
Publication series
Series | Proceedings of the AAAI Conference on Artificial Intelligence |
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Number | 5 |
Volume | 36 |
ISSN | 2159-5399 |
External IDs
ORCID | /0000-0001-9936-0943/work/142238127 |
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Mendeley | 32449263-19dd-317c-881b-683be022eb2a |
unpaywall | 10.1609/aaai.v36i5.20489 |