Hostname: page-component-7b7567c8c-wxvwp Total loading time: 0 Render date: 2026-11-15T15:44:17.091Z Has data issue: false hasContentIssue false

CASP solutions for planning in hybrid domains

Published online by Cambridge University Press:  04 July 2017

MARCELLO BALDUCCINI
Affiliation:
Saint Joseph's University, Department of Decision and Support Services, 5600 City Avenue, Philadelphia, PA 19131, USA (e-mail: marcello.balduccini@gmail.com)
DANIELE MAGAZZENI
Affiliation:
King's College London, Department of Informatics, The Strand, London, WC2R 2LS, England (e-mail: daniele.magazzeni@kcl.ac.uk)
MARCO MARATEA
Affiliation:
University of Genoa, Italy (e-mail: marco@dibris.unige.it)
EMILY C. LEBLANC
Affiliation:
Drexel University, Computer Science Department, 3141 Chestnut Avenue, PA 19104, USA (e-mail: ecl38@drexel.edu)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

Constraint answer set programming (CASP) is an extension of answer set programming that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the ezcsp CASP solver in order to solve CASP programs arising from PDDL+ domains. An experimental analysis, performed on well-known linear and non-linear variants of PDDL+ domains, involving various configurations of the ezcsp solver, other CASP solvers, and PDDL+ planners, shows the viability of our solution.

Information

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2017