How social learning enhances-or undermines-efficiency and flexibility in collective decision-making under uncertainty.

ABSTRACT: Balancing efficiency and flexibility in collective decision-making is increasingly critical in modern societies characterized by rapid sociocultural and technological change. Recent research in cognitive neuroscience has proposed two contrasting computational algorithms for social learning: value shaping (VS) and decision biasing (DB). VS posits that others' choices serve as "pseudo-rewards" that directly shape an observer's valuations, leading them to prefer popular options even in the absence of outcome feedback. In contrast, DB confines the influence of social information to behavior-observers may imitate popular actions, but they update their valuations solely through personal experience. Although both algorithms facilitate individual adaptation under uncertainty, their interactive dyn

SUBMITTER: Suganuma H 

PROVIDER: S-EPMC12685029 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature