An Efficient Approach for Rule Matching in Production System based on Multi-Agent

被引:0
|
作者
Yao, Jiaqi [1 ]
机构
[1] Natl Key Lab Sci & Technol Blind Signal Proc, Chengdu, Peoples R China
关键词
consponent; production system; Rete algorithm; Multi-Agent;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Production system, which is also named as rule engine, has been widely used in artificial intelligence. Rete algorithm is the most popular rule-match algorithm, which speeds up the whole procedure by sharing the conditions among the productions and storing the temporary results. However, when the size of rules and facts continues to grow, Rete algorithm becomes computationally expensive and slow. In this paper, we propose an efficient approach for rule matching in production system based on Multi-Agent, which treats each node in rete algorithm as an agent, and every agent individually performs its own computational tasks and shares the state by passing messages. We also introduce indexes on tokens to accelerate the match and design a mechanism to balance the computational tasks among agents. Filially we conduct experiment to show its efficiency.
引用
收藏
页码:378 / 381
页数:4
相关论文
共 50 条
  • [31] Requests Management for Smartphone-Based Matching Applications Using a Multi-agent Approach
    Simonin, Gilles
    O'Sullivan, Barry
    LEARNING AND INTELLIGENT OPTIMIZATION (LION 10), 2016, 10079 : 173 - 186
  • [32] Concept of a Multi-agent Based Decentralized Production System for the Automotive Industry
    Blesing, Christian
    Luensch, Dennis
    Stenzel, Jonas
    Korth, Benjamin
    ADVANCES IN PRACTICAL APPLICATIONS OF CYBER-PHYSICAL MULTI-AGENT SYSTEMS: THE PAAMS COLLECTION, PAAMS 2017, 2017, 10349 : 19 - 30
  • [33] A Genetic Multi-Agent Rule Induction System for Stream Data
    Kim, Jinhwa
    Won, Chaehwan
    Byeon, Hyeonsu
    NCM 2008: 4TH INTERNATIONAL CONFERENCE ON NETWORKED COMPUTING AND ADVANCED INFORMATION MANAGEMENT, VOL 2, PROCEEDINGS, 2008, : 54 - 58
  • [34] A Hybrid System Dynamic Production Scheduling Method Based On Multi-Agent
    Ma, Xiaofeng
    2012 INTERNATIONAL CONFERENCE ON INDUSTRIAL CONTROL AND ELECTRONICS ENGINEERING (ICICEE), 2012, : 179 - 181
  • [35] Multi-agent based control kernel for flexible automated production system
    Liu, SH
    Fu, LC
    Yang, JH
    1998 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-4, 1998, : 2134 - 2139
  • [36] The Topology Optimization Rule for Multi-Agent System Fast Consensus
    Zhang, Miao Miao
    Yun, Hong Quan
    Ju, Wen
    2018 IEEE CSAA GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2018,
  • [37] A multi-agent approach to distribution system restoration
    Nagata, T
    Tao, Y
    Sasaki, H
    Fujita, H
    2003 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-4, CONFERENCE PROCEEDINGS, 2003, : 655 - 660
  • [38] An improved learning approach in Multi-agent system
    Liang, Jun
    Cheng, Xian-Yi
    PROCEEDINGS OF 2008 INTERNATIONAL COLLOQUIUM ON ARTIFICIAL INTELLIGENCE IN EDUCATION, 2008, : 6 - 10
  • [39] A multi-agent approach to power system restoration
    Nagata, T
    Watanabe, H
    Ohno, M
    Sasaki, H
    2000 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS I-III, PROCEEDINGS, 2000, : 1551 - 1556
  • [40] A multi-agent approach to power system restoration
    Nagata, T
    Sasaki, H
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) : 457 - 462