Three-way decision-driven adaptive stochastic consensus dynamics for large-scale group decision making
Date:2026-10-24 clicks:
Journal:Information Sciences
Abstract:Large-scale group decision making needs consensus rules that are robust to uncertainty yet easy to interpret. We propose TWD-SCD, a consensus framework built on three-way decision. At each step every decision maker is placed in a positive, boundary, or negative region based on its distance from the group, and each region triggers a different update: keep the opinion, mix it mildly with the group mean, or average it over the social network. A lightweight Q-learning policy tunes the region thresholds online. We analyze the fixed-threshold kernel and the learning policy separately. For the fixed-threshold kernel, we give concrete, checkable conditions on the network and the thresholds under which a contraction holds, yielding almost-sure consensus when noise decays and a bounded error floor when noise is constant. A mean-field argument predicts a critical threshold, and a residual test bounds how well cooperative and non-cooperative decision makers can be told apart before consensus erases the evidence. We evaluate TWD-SCD against eight baselines on random graphs (up to �� =3000), with further tests on the real email-Eu-core topology and on MovieLens ratings. It matches DeGroot’s consensus level at lower adjustment cost and lower variance under non-cooperative behavior.
Indexed by:Journal paper
Document Code:12054
Volume:759
Translation or Not:no
Date of Publication:2026-09-29
Included Journals:SCI
First Author:Bo Sun
Co-author:Chunmao Jiang,Ruyi Ye,Hao Zhang