Let's learn their language? a case for planning with automata-network languages from model checking

Jörg Hoffmann, Holger Hermanns, Michaela Klauck, Marcel Steinmetz, Erez Karpas, Daniele Magazzeni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

It is widely known that AI planning and model checking are closely related. Compilations have been devised between various pairs of language fragments. What has barely been voiced yet, though, is the idea to let go of one's own modeling language, and use one from the other area instead. We advocate that idea here - to use automata-network languages from model checking instead of PDDL - motivated by modeling difficulties relating to planning agents surrounded by exogenous agents in complex environments. One could, of course, address this by designing additional extended planning languages. But one can also leverage decades of work on modeling in the formal methods community, creating potential for deep synergy and integration with their techniques as a side effect. We believe there's a case to be made for the latter, as one modeling alternative in planning among others.

Original languageEnglish
Title of host publicationAAAI 2020 - 34th AAAI Conference on Artificial Intelligence
Pages13569-13575
Number of pages7
ISBN (Electronic)9781577358350
StatePublished - 2020
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 7 Feb 202012 Feb 2020

Publication series

NameAAAI 2020 - 34th AAAI Conference on Artificial Intelligence

Conference

Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York
Period7/02/2012/02/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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