Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3305275.3305276acmotherconferencesArticle/Chapter ViewAbstractPublication PagesisbdaiConference Proceedingsconference-collections
short-paper

Norm-based Enterprise Agent Intelligence Design

Published: 29 December 2018 Publication History

Abstract

In the fierce market competition, enterprises constantly evolve themselves according to market requirements to better survive and develop. This paper establishes a multi-agent enterprise model, decomposes the complex enterprise system into multiple Agent entities to form a multi-agent system (MAS), and jointly solves the overall goals of the system by multi-agents. Using genetic algorithms and learning classifiers, the concept of norm in organization semiotics was introduced. Then enterprise agents was objectively controlled and constrained by the norm based on the complex semantics of the specification. On this basis, a parallel, rule-based, enterprise intelligence was developed, which can be automatically updated with rules and reflects the subjective initiative of agents under the environment. Finally, a case study was carried out on the Swarm simulation platform. The simulation results show that the design of the enterprise agent intelligence provides support for selection of the dynamic behavior of the enterprise agent.

References

[1]
Ajournalarticle, Tianchen Huang, Jingcai Han(2005). Analysis and Modeling of Complex Adaptive System Based on Agent Technology. Computer Simulation, 22(9), 58--60.
[2]
Cmagazinearticle, Xiaomu Zhou(2000). Implicit order - adaptability creates complexity. Shanghai Science and Technology Education Press.
[3]
Cmagazinearticle, Liming Jia, Gang Liu&Yong Qin(2007). Dynamic Cooperative Task Solving Based on Intelligent Agent. Science Press.
[4]
Dbookreference, Xianguo Liu(2008). Research on Collaborative Design System Based on Multi-Agent. Harbin University of Science and Technology.
[5]
Ajournalarticle, Ying Deng, NanNan Yan(2008). Research on Application of Multi-Agent Technology in Production Scheduling of Container Terminals. China Water Transport, 8(7), 7--9.
[6]
Fchapter, Gazendam H, Liu K.(2004). The Evolution of Organisational Semiotics - A Brief Review of the Contribution of Ronald Stamper1, Studies in Organisational.
[7]
Ajournalarticle, Jun Zhao, Renchu Gan(2005). The Evolution of Organisational Semiotics - A Brief Review of the Contribution of Ronald Stamper1. Studies in Organisational.

Index Terms

  1. Norm-based Enterprise Agent Intelligence Design

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ISBDAI '18: Proceedings of the International Symposium on Big Data and Artificial Intelligence
    December 2018
    365 pages
    ISBN:9781450365703
    DOI:10.1145/3305275
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 December 2018

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Agent Intelligence
    2. Genetic Algorithm
    3. Norm
    4. Swarm Simulation

    Qualifiers

    • Short-paper
    • Research
    • Refereed limited

    Conference

    ISBDAI '18

    Acceptance Rates

    ISBDAI '18 Paper Acceptance Rate 70 of 340 submissions, 21%;
    Overall Acceptance Rate 70 of 340 submissions, 21%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 78
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 10 Nov 2024

    Other Metrics

    Citations

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media