Automated planning with ontologies under coherence update semantics (Extended Version)
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909701200936960 |
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| author | Borgwardt, Stefan Nhu, Duy Röger, Gabriele |
| author_facet | Borgwardt, Stefan Nhu, Duy Röger, Gabriele |
| contents | Standard automated planning employs first-order formulas under closed-world semantics to achieve a goal with a given set of actions from an initial state. We follow a line of research that aims to incorporate background knowledge into automated planning problems, for example, by means of ontologies, which are usually interpreted under open-world semantics. We present a new approach for planning with DL-Lite ontologies that combines the advantages of ontology-based action conditions provided by explicit-input knowledge and action bases (eKABs) and ontology-aware action effects under the coherence update semantics. We show that the complexity of the resulting formalism is not higher than that of previous approaches and provide an implementation via a polynomial compilation into classical planning. An evaluation of existing and new benchmarks examines the performance of a planning system on different variants of our compilation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_15120 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automated planning with ontologies under coherence update semantics (Extended Version) Borgwardt, Stefan Nhu, Duy Röger, Gabriele Artificial Intelligence Logic in Computer Science Standard automated planning employs first-order formulas under closed-world semantics to achieve a goal with a given set of actions from an initial state. We follow a line of research that aims to incorporate background knowledge into automated planning problems, for example, by means of ontologies, which are usually interpreted under open-world semantics. We present a new approach for planning with DL-Lite ontologies that combines the advantages of ontology-based action conditions provided by explicit-input knowledge and action bases (eKABs) and ontology-aware action effects under the coherence update semantics. We show that the complexity of the resulting formalism is not higher than that of previous approaches and provide an implementation via a polynomial compilation into classical planning. An evaluation of existing and new benchmarks examines the performance of a planning system on different variants of our compilation. |
| title | Automated planning with ontologies under coherence update semantics (Extended Version) |
| topic | Artificial Intelligence Logic in Computer Science |
| url | https://arxiv.org/abs/2507.15120 |