Prosocial learning: Model-based or model-free?

Parisa Navidi, Sepehr Saeedpour, Sara Ershadmanesh, Mostafa Miandari Hossein and Bahador Bahrami

PLOS ONE, 2023, vol. 18, issue 6, 1-15

Abstract: Prosocial learning involves the acquisition of knowledge and skills necessary for making decisions that benefit 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.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0287563

DOI: 10.1371/journal.pone.0287563

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