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Australian Joint Conference on Artificial Intelligence

AI 2002: AI 2002: Advances in Artificial Intelligence pp 203–212Cite as

Adaptive Multi-agent Decision Making Using Analytical Hierarchy Process

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2557))

Abstract

In multi-agent decision-making problems, we should treat all the participating agents with no partiality. In this paper, we seek to elicit the cooperation level from each agent’s inner world. This benefit would be gained by the reasonable preference values to each alternative in the viewpoint of the group. Besides, we propose a methodology to adapt group’s preference functions. It can make all the participating agents have the chances to pick up the most favorite choice after several rounds of decision-making process.

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References

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Author information

Authors and Affiliations

  1. Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan, ROC

    Chen Juei-Nan & Huang Yueh-Min

  2. Department of Computer Science and Information Engineering, TungHai University, Taichung, Taiwan, ROC

    William C. Chu

Authors
  1. Chen Juei-Nan
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  2. Huang Yueh-Min
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  3. William C. Chu
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Editor information

Editors and Affiliations

  1. Australian Defence Force Academy, University of New South Wales, ACT 2600, Canberra, Australia

    Bob McKay

  2. Computer Science Laboratory, Australian National University, RSISE Building, ACT 0200, Canberra, Australia

    John Slaney

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© 2002 Springer-Verlag Berlin Heidelberg

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Cite this paper

Juei-Nan, C., Yueh-Min, H., Chu, W.C. (2002). Adaptive Multi-agent Decision Making Using Analytical Hierarchy Process. In: McKay, B., Slaney, J. (eds) AI 2002: Advances in Artificial Intelligence. AI 2002. Lecture Notes in Computer Science(), vol 2557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36187-1_18

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  • DOI: https://doi.org/10.1007/3-540-36187-1_18

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00197-3

  • Online ISBN: 978-3-540-36187-9

  • eBook Packages: Springer Book Archive

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