IEEE Intelligent Systems, 20(2), pp. 62-72

Reference Nareyek, A.; Fourer, R.; Freuder, E. C.; Giunchiglia, E.; Goldman, R. P.; Kautz, H.; Rintanen, J.; and Tate, A. 2005.
Constraints and AI Planning.
IEEE Intelligent Systems, 20(2), 62-72.

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.

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ATTENTION:
The editing by the publisher introduced some errors. Besides the authors' order (see above for correct order), the redraw of Figure 2 is flawed and makes it very hard to understand the corresponding section. Here is a corrected version:

Reference	Nareyek, A.; Fourer, R.; Freuder, E. C.; Giunchiglia, E.; Goldman, R. P.; Kautz, H.; Rintanen, J.; and Tate, A. 2005. Constraints and AI Planning. IEEE Intelligent Systems, 20(2), 62-72.
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.
Download	[PDF; 0.99 Mb]
ATTENTION:	The editing by the publisher introduced some errors. Besides the authors' order (see above for correct order), the redraw of Figure 2 is flawed and makes it very hard to understand the corresponding section. Here is a corrected version: