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A Semisupervised Multiagent System Model to Support Consensus-Reaching Processes
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AI
DOI：10.1109/TFUZZ.2013.2272588.png)
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Abstract
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Consensus reaching processes as part of solving group decision-making problems attempt to reach a mutual agreement in the group before making a decision. Most consensus models and consensus support systems that are proposed in the literature present some noticeable drawbacks: the need for constant human supervision by experts to guarantee an effective process and the difficulty to manage large groups of experts, which are increasingly common in current decisions and may imply a higher cost and complexity to carry out such processes. In order to overcome these problems, this paper presents a novel consensus support system based on the multiagent system paradigm, which automates and supports consensus reaching processes by providing agents with the necessary degree of autonomy to conduct discussion processes by themselves, with a semisupervised methodology. The main novelty of such a system is the agent semisupervised autonomy approach it incorporates, which lets agents conduct most of the discussion process by themselves and allows them to interact with their corresponding human experts under certain circumstances in which human supervision might be convenient and necessary.
Keywords:
Consensus reaching process (CRP)
fuzzy preference relation
group decision making (GDM)
multiagent system
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