Skip to main navigation Skip to search Skip to main content

The performance optimization of CLIPS

  • Yuxin Ding*
  • , Qing Wang
  • , Jiahua Huang
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

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

Abstract

CLIPS is an expert system tool which provides a complete environment for the construction of rule and/or object based expert systems. Because of its portability, extensibility, capabilities, and low-cost, CLIPS has received widespread acceptance. As a production system CLIPS's performance rapidly decreases as the number of working memory elements increases. To address this problem, this paper is aimed at speeding up CLIPS in the case of dealing with large amount of facts and changeable facts. In this paper two measures are adopted to improve CLIP's performance, firstly RETE algorithm which is used as the rule condition-testing algorithm in CLIPS are replaced with TREAT algorithm. Secondly some practical techniques are employed when implementing TREAT algorithm such as recording partial matches, hashing the alpha node, adding rule group. Experimental results show that the two measures can effectively improve CLIPS's performance.

Original languageEnglish
Title of host publicationProceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
Pages417-421
Number of pages5
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009 - Shenyang, China
Duration: 12 Aug 200914 Aug 2009

Publication series

NameProceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
Volume1

Conference

Conference2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
Country/TerritoryChina
CityShenyang
Period12/08/0914/08/09

Keywords

  • CLIPS
  • Optimization
  • Production system
  • RETE
  • TREAT

Fingerprint

Dive into the research topics of 'The performance optimization of CLIPS'. Together they form a unique fingerprint.

Cite this