{"ID":2892691,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.15120","arxiv_id":"2507.15120","title":"Automated planning with ontologies under coherence update semantics (Extended Version)","abstract":"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.","short_abstract":"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 i...","url_abs":"https://arxiv.org/abs/2507.15120","url_pdf":"https://arxiv.org/pdf/2507.15120v2","authors":"[\"Stefan Borgwardt\",\"Duy Nhu\",\"Gabriele Röger\"]","published":"2025-07-20T20:49:21Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.LO\"]","methods":"[]","has_code":false}