Lotinac, DamirSegovia-Aguas, JavierJiménez, SergioJonsson, Anders, 1973-2016-07-212016-07-212016Lotinac D, Segovia-Aguas J, Jiménez S, Jonsson A. Automatic generation of high-level state features for generalized planning. In: Kambhampati S, editor. Proceedings of the 25th International Joint Conference on Artificial Intelligence; 2016 July 9-15; New York, United States. Palo Alto: AAAI Press; 2016. p. 3199-3205.http://hdl.handle.net/10230/27096In many domains generalized plans can only/nbe computed if certain high-level state features,/ni.e. features that capture key concepts to accurately/ndistinguish between states and make good decisions,/nare available. In most applications of generalized/nplanning such features are hand-coded by/nan expert. This paper presents a novel method/nto automatically generate high-level state features/nfor solving a generalized planning problem. Our/nmethod extends a compilation of generalized planning/ninto classical planning and integrates the computation/nof generalized plans with the computation/nof features, in the form of conjunctive queries. Experiments/nshow that we generate features for diverse/ngeneralized planning problems and hence,/ncompute generalized plans without providing a/nprior high-level representation of the states. We/nalso bring a new landscape of challenging benchmarks/nto classical planning since our compilation/nnaturally models classification tasks as classical/nplanning problems.application/pdfeng© 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org)info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess