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Planning with Incomplete Information in Quantified Answer Set Programming

Published online by Cambridge University Press:  24 September 2021

JORGE FANDINNO Open the ORCID record for JORGE FANDINNO [Opens in a new window] ,
FRANCOIS LAFERRIERE ,
JAVIER ROMERO Open the ORCID record for JAVIER ROMERO [Opens in a new window] ,
TORSTEN SCHAUB Open the ORCID record for TORSTEN SCHAUB [Opens in a new window]  and
TRAN CAO SON Open the ORCID record for TRAN CAO SON [Opens in a new window]
JORGE FANDINNO
Affiliation:
Omaha State University, USA University of Potsdam, Germany (e-mail: jfandinno@unomaha.edu)
FRANCOIS LAFERRIERE
Affiliation:
University of Potsdam, Germany (e-mails: francois@cs.uni-potsdam.de, javier@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de)
JAVIER ROMERO
Affiliation:
University of Potsdam, Germany (e-mails: francois@cs.uni-potsdam.de, javier@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de)
TORSTEN SCHAUB
Affiliation:
University of Potsdam, Germany (e-mails: francois@cs.uni-potsdam.de, javier@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de)
TRAN CAO SON
Affiliation:
New Mexico State University, USA (e-mail: tson@cs.nmsu.edu)
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Abstract

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We present a general approach to planning with incomplete information in Answer Set Programming (ASP). More precisely, we consider the problems of conformant and conditional planning with sensing actions and assumptions. We represent planning problems using a simple formalism where logic programs describe the transition function between states, the initial states and the goal states. For solving planning problems, we use Quantified Answer Set Programming (QASP), an extension of ASP with existential and universal quantifiers over atoms that is analogous to Quantified Boolean Formulas (QBFs). We define the language of quantified logic programs and use it to represent the solutions different variants of conformant and conditional planning. On the practical side, we present a translation-based QASP solver that converts quantified logic programs into QBFs and then executes a QBF solver, and we evaluate experimentally the approach on conformant and conditional planning benchmarks.

Keywords

answer set programmingplanningquantified logics
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 21 , Issue 5: 37th International Conference on Logic Programming Special Issue I , September 2021 , pp. 663 - 679
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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