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Planning by Guided Hill-Climbing

  • Seyed Ali Akramifar
  • Gholamreza Ghassem-Sani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4827)

Abstract

This paper describes a novel approach will be called guided hill climbing to improve the efficiency of hill climbing in the planning domains. Unlike simple hill climbing, which evaluates the successor states without any particular order, guided hill climbing evaluates states according to an order recommended by an auxiliary guiding heuristic function. Guiding heuristic function is a self-adaptive and cost effective function based on the main heuristic function of hill climbing. To improve the performance of the method in various domains, we defined several heuristic functions and created a mechanism to choose appropriate functions for each particular domain. We applied the guiding method to the enforced hill climbing, which has been used by the Fast Forward planning system (FF). The results show a significant improvement in the efficiency of FF in a number of domains.

Keywords

Successor State Hill Climbing Heuristic Function Heuristic Selection Logistics Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Seyed Ali Akramifar
    • 1
  • Gholamreza Ghassem-Sani
    • 1
  1. 1.Computer Engineering Department, Sharif University of Technology, P.O. Box 11365-9517, TehranIran

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