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Addressee Learning and Message Interception for communication load reduction in multiple robot environments

  • Learning, Communication and Understanding
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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments (LDAIS 1996, LIOME 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1221))

Abstract

This paper describes communication load reduction on task negotiation with Contract Net Protocol for multiple autonomous mobile robots. We have developed Lemming[5, 6, 7], a task negotiation system with low communication load for multiple autonomous mobile robots. For controlling multiple robots, Contract Net Protocol(CNP)[10] is useful, but the broadcast of the Task Announcement messages on CNP tends to consume much communication load. In order to overcome this problem Lemming learns proper addressees for the Task Announcement messages with Case-Based Reasoning[3] so as to suppress the broadcast. The learning method is called Addressee Learning. However the learning method causes inefficient task execution. An extension of Lemming with Message Interception which enables the system to execute tasks more efficiently is reported.

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References

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Author information

Authors and Affiliations

  1. Anzai Laboratory, Department of Computer Science, Keio University, 3-14-1, Hiyoshi, Kohoku, 223, Yokohama, Japan

    Takuya Ohko & Yuichiro Anzai

  2. Presto/Electrotechnical Laboratory, MITI, 1-1-4, Umezono, 305, Tsukuba, Japan

    Kazuo Hiraki

Authors
  1. Takuya Ohko
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  2. Kazuo Hiraki
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  3. Yuichiro Anzai
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Editor information

Gerhard Weiß

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© 1997 Springer-Verlag Berlin Heidelberg

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Ohko, T., Hiraki, K., Anzai, Y. (1997). Addressee Learning and Message Interception for communication load reduction in multiple robot environments. In: Weiß, G. (eds) Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments. LDAIS LIOME 1996 1996. Lecture Notes in Computer Science, vol 1221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62934-3_52

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  • DOI: https://doi.org/10.1007/3-540-62934-3_52

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62934-4

  • Online ISBN: 978-3-540-69050-4

  • eBook Packages: Springer Book Archive

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