Proceedings of the Annual Meeting of the Cognitive Science Society

Humans are resistant to changing their beliefs even in the face of disconfirming evidence. The Bayesian brain theory suggests that we should update our beliefs optimally in light of new evidence, but recent research indicates that belief formation is far from the Bayesian ideal. Individuals can exhibit "stronger-than-rational" updating or be resistant to revising their beliefs. The present study proposes a novel paradigm to explore perceptions and preferences for belief updating patterns in stable and dynamic stochastic environments, using an advice-taking paradigm. In an experiment (N=567) based on a fishing task, we introduce three advisor characters representing formal updating models: Bayesian, Volatile and Rigid. We find that participants exhibit higher trust for the Bayesian advisor than the Rigid advisor, in the stable but not changeable environment conditions. In the changeable environment, participants exhibit higher trust for the Volatile advisor, compared to both the Bayesian and Rigid advisors. The findings also suggest that participants' own learning closely mimics the pattern of the Volatile model. This study illustrates that people can differentiate between Bayesian updating, and its "stronger-than" and "weaker-than" variations, and exhibit preferences for these updating patterns, in different environment structures.