English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

State constraints in AI Planning globally restrict the legal environmentstates. Standard planning languages make closed-domain and closed-worldassumptions. Here we address open-world state constraints formalized byplanning over a description logic (DL) ontology. Previously, this combinationof DL and planning has been investigated for the light-weight DL DL-Lite. Herewe propose a novel compilation scheme into standard PDDL with derivedpredicates, which applies to more expressive DLs and is based on therewritability of DL queries into Datalog with stratified negation. We alsoprovide a new rewritability result for the DL Horn-ALCHOIQ, which allows us toapply our compilation scheme to quite expressive ontologies. In contrast, weshow that in the slight extension Horn-SROIQ no such compilation is possibleunless the weak exponential hierarchy collapses. Finally, we show that ourapproach can outperform previous work on existing benchmarks for planning withDL ontologies, and is feasible on new benchmarks taking advantage of moreexpressive ontologies. That is an extended version of a paper accepted at AAAI22.

Expressivity of Planning with Horn Description Logic Ontologies (Technical Report)