Constraints and AI Planning

Authors:
Alexander Nareyek;Eugene C. Freuder;Robert Fourer;Enrico Giunchiglia;Robert P. Goldman;Henry Kautz;Jussi Rintanen;Austin Tate
Affiliations:
University College Cork;University College Cork;Northwestern University;University of Genova;Smart Information Flow Technologies;University of Washington;Albert-Ludwigs-University Freiburg;University of Edinburgh
Venue:
IEEE Intelligent Systems
Year:
2005

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Abstract

Tackling real-world planning problems often requires considering various types of constraints, ranging from simple numerical comparators to complex resources. This article provides an overview of how to solve planning tasks within general constraint-solving frameworks, such as propositional satisfiability, integer programming, and constraint programming. In many cases, the complete planning problem can be cast in these frameworks.