Reinforcement Learning-Based Feedback and Weight-Adjustment Mechanisms for Consensus Reaching in Group Decision Making-Reference-Cited by-同舟云学术

Reinforcement Learning-Based Feedback and Weight-Adjustment Mechanisms for Consensus Reaching in Group Decision Making

Published:2023-04 Issue:4 Volume:53 Page:2456-2468
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Hassani Hossein¹^ORCID,Razavi-Far Roozbeh¹^ORCID,Saif Mehrdad¹^ORCID,Herrera-Viedma Enrique²^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Windsor, Windsor, Canada

2. Department of Computer Science and AI, Andalusian Research Institute on Data Science and Computational Intelligence, University of Granada, Granada, Spain

Funder

Natural Sciences and Engineering Research Council of Canada

Agencia Estatal de Investigación

Andalusian Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221021/10073970/09928222.pdf?arnumber=9928222

Reference50 articles.

1. A framework for group decision making with multiplicative trapezoidal fuzzy preference relations

2. Algorithms to Detect and Rectify Multiplicative and Ordinal Inconsistencies of Fuzzy Preference Relations

3. Optimization-based group decision making using interval-valued intuitionistic fuzzy preference relations

4. Group decision making based on multiplicative consistency-and-consensus preference analysis for incomplete q-rung orthopair fuzzy preference relations

5. Group Decision Making Based on Flexibility Degree of Fuzzy Numbers Under a Confidence Level

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