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Title: Hybrid AcE: Combining Search Directions for Heuristic Planning
Author(s): D. Vrakas, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (26 pages).
Appeared in: Computational Intelligence, Blackwell, 21(3), pp. 306-331, 2005.
Abstract: One of the most promising trends in Domain-Independent AI Planning, nowadays, is state-space heuristic planning. The planners of this category construct general but efficient heuristic functions, which are used as a guide to traverse the state space either in a forward or in a backward direction. Although specific problems may favor one or the other direction, there is no clear evidence why any of them should be generally preferred. This paper presents Hybrid-AcE, a domain-independent planning system that combines search in both directions utilizing a complex criterion that monitors the progress of the search, to switch between them. Hybrid AcE embodies two powerful domain-independent heuristic functions extending one of the AcE planning systems. Moreover, the system is equipped with a fact-ordering technique and two methods for problem simplification that limit the search space and guide the algorithm to the most promising states. The bi-directional system has been tested on a variety of problems adopted from the AIPS planning competitions with quite promising results.
See also :

        This paper has been cited by the following:

1 A. D. Mali, M. Tang, “State-space planning with variants of A*”, International Journal on Artificial Intelligence Tools, 15 (3), 2006, pp. 433-464.
2 O. Hatzi, "Web Service Composition through AI Planning", PhD Thesis, Department of Informatics and Telematics, Harokopeio University, 2009
3 Y. Chu, Z. Li, Y. Su, Z. Pizlo, "Heuristics in Problem Solving: The Role of Direction in Controlling Search Space", The Journal of Problem Solving • volume 3, no. 1, 2010