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Constraints and AI Planning
March/April 2005 (vol. 20 no. 2)
pp. 62-72
Alexander Nareyek, University College Cork
Eugene C. Freuder, University College Cork
Robert Fourer, Northwestern University
Enrico Giunchiglia, University of Genova
Robert P. Goldman, Smart Information Flow Technologies
Henry Kautz, University of Washington
Jussi Rintanen, Albert-Ludwigs-University Freiburg
Austin Tate, University of Edinburgh
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.
Index Terms:
planning, constraint programming, propositional satisfiability, integer programming
Citation:
Alexander Nareyek, Eugene C. Freuder, Robert Fourer, Enrico Giunchiglia, Robert P. Goldman, Henry Kautz, Jussi Rintanen, Austin Tate, "Constraints and AI Planning," IEEE Intelligent Systems, vol. 20, no. 2, pp. 62-72, March-April 2005, doi:10.1109/MIS.2005.25
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