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Workshops on Real-World Applications of Evolutionary Computation

EvoWorkshops 2000: Real-World Applications of Evolutionary Computing pp 255–266Cite as

A Communication Architecture for Multi-Agent Learning Systems

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1803))

Abstract

This paper presents a simple communication architecture for Multi-Agent Learning Systems. The service provided by the communication architecture allows each agent to connect to the user interface, the application and the other agents. The communication architecture is implemented using TCP/IP. An application example in a simplified traffic environment shows that the communication architecture can provide reliable and efficient communication services for Multi-Agent Learning Systems.

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Author information

Authors and Affiliations

  1. Intelligent Computer Systems Centre Faculty of Computer Studies and Mathematics, University of the West of England, Bristol, BS16 1QY, UK

    N. Ireson, Y. J. Cao, L. Bull & R. Miles

Authors
  1. N. Ireson
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  2. Y. J. Cao
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  3. L. Bull
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  4. R. Miles
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, University of Parma, Parco delle Scienze 181/a, 43100, Parma, Italy

    Stefano Cagnoni

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© 2000 Springer-Verlag Berlin Heidelberg

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Ireson, N., Cao, Y.J., Bull, L., Miles, R. (2000). A Communication Architecture for Multi-Agent Learning Systems. In: Cagnoni, S. (eds) Real-World Applications of Evolutionary Computing. EvoWorkshops 2000. Lecture Notes in Computer Science, vol 1803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45561-2_25

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  • DOI: https://doi.org/10.1007/3-540-45561-2_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67353-8

  • Online ISBN: 978-3-540-45561-5

  • eBook Packages: Springer Book Archive

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