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Vicarious learning: model-based or model-free?


Ershadmanesh,  S       
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Navidi, P., Saeedpou, S., Ershadmanesh, S., Hossein, M., & Bahrami, B. (submitted). Vicarious learning: model-based or model-free?

Cite as: https://hdl.handle.net/21.11116/0000-000D-0C87-E
Vicarious learning refers to learning to make decisions on behalf of others. We asked if, in the context of value-based decision-making, there is any difference between learning strategies for oneself vs. for others. We implemented a 2-step reinforcement learning paradigm in which participants learned, in separate blocks, to make decisions for themselves or for a present other confederate who evaluated their performance. We replicated the canonical features of the model-based and model-free reinforcement learning in our results. The behaviour of the majority of participants was best explained by a mixture of the model-based and model-free control, while most participants relied more heavily on MB control, and this strategy enhanced their learning success. Regarding our key self-other hypothesis, we did not find any significant difference between the behavioural performances nor in the model-based parameters of learning when comparing self and other conditions.