Exploiting Meta-Cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation. (arXiv:2201.08247v1 [cs.LG])

The outcome of a collective decision-making process, such as crowdsourcing,
often relies on the procedure through which the perspectives of its individual
members are aggregated. Popular aggregation methods, such as the majority rule,
often fail to produce the optimal result, especially in high-complexity tasks.
Methods that rely on meta-cognitive information, such as confidence-based
methods and the Surprisingly Popular Option, had shown an improvement in
various tasks. However, there is still a significant number of cases with no
optimal solution. Our …

arxiv cognitive decision learning machine meta