Humans flexibly integrate social information despite interindividual differences in reward
Alexandra Witt,
Wataru Toyokawa,
Kevin N. Lala
et al.
Abstract:There has been much progress in understanding human social learning, including recent studies integrating social information into the reinforcement learning framework. Yet previous studies often assume identical payoffs between observer and demonstrator, overlooking the diversity of social information in real-world interactions. We address this gap by introducing a socially correlated bandit task that accommodates payoff differences among participants, allowing for the study of social learning under more reali… Show more
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