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A Multi-agent Decision-Theoretic Rough Set Model

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Rough Set and Knowledge Technology (RSKT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6401))

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Abstract

The decision-theoretic rough set (DTRS) model considers cost and risk factors when classifying an equivalence class into a particular region. Using DTRS, informative decisions with rough rules can be made. The current research has a focus on single agent decision makings. We propose a multi-agent DTRS model in this paper. This model seeks synthesized or consensus decision when there are multiple sets of decision preferences and criteria adopted by different agents. A set of rough decision rules that are satisfied by multiple agents can be derived from the multi-agent decision-theoretic rough set model.

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Author information

Authors and Affiliations

  1. School of Mathematics, Physics & Information Science, Zhejiang Ocean University, Zhoushan, Zhejiang, P.R. China, 316004

    Xiaoping Yang

  2. Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2

    Xiaoping Yang & Jingtao Yao

Authors
  1. Xiaoping Yang
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  2. Jingtao Yao
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Editor information

Editors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, 100044, Beijing, China

    Jian Yu

  2. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  3. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, Nova Scotia, Canada

    Pawan Lingras

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, China

    Guoyin Wang

  5. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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Yang, X., Yao, J. (2010). A Multi-agent Decision-Theoretic Rough Set Model. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_96

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  • DOI: https://doi.org/10.1007/978-3-642-16248-0_96

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16247-3

  • Online ISBN: 978-3-642-16248-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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