An action guided constraint satisfaction technique for planning problem

Xiao Jiang, Pingyuan Cui, Rui Xu*, Ai Gao, Shengying Zhu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, we discuss how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable selected procedure in constraint satisfaction problems. Through theoretical analysis, this technique is prior an order of magnitude in variable select procedure over the ordinary heuristic technique and can be used in constraint-programmed planning problem generally. With the simulation experiments it shows that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version.

Original languageEnglish
Title of host publicationProceedings of 2016 IEEE 15th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016
EditorsKostas Plataniotis, Bernard Widrow, Newton Howard, Lotfi A. Zadeh, Yingxu Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages167-173
Number of pages7
ISBN (Electronic)9781509038466
DOIs
Publication statusPublished - 21 Feb 2017
Event15th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016 - Stanford, United States
Duration: 22 Aug 201623 Aug 2016

Publication series

NameProceedings of 2016 IEEE 15th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016

Conference

Conference15th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2016
Country/TerritoryUnited States
CityStanford
Period22/08/1623/08/16

Keywords

  • Action guided
  • Constraint satisfaction
  • Planning
  • Variable selected

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