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Computational mechanisms underlying learning and recalling of trustworthy partners


Bellucci,  G       
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;


Dayan,  P       
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bellucci, G., & Dayan, P. (2022). Computational mechanisms underlying learning and recalling of trustworthy partners. Poster presented at Annual Meeting of the Society for NeuroEconomics (SNE 2022), Arlington, VA, USA.

Cite as: https://hdl.handle.net/21.11116/0000-000B-0D06-1
Learning the personalities of others is fundamental for navigating social environments. Previous work has identified which traits are central to the impression of trustworthiness, but how these traits are inferred and remembered to influence social decisions in repeated interactions is underexplored. Objectives We studied how individuals learn another person's trust attitude, and tested memory effects on prosocial behaviors. We used a novel modification of a multi-round investment game in which participants interact with multiple partners. On each trial, participants, as trustees, need first to choose one of two teams from which an investor is randomly chosen to play. Importantly, each investor sports a trial-unique avatar that participants can use to remember their interaction. Methods Team members have different trust attitudes which participants can infer. They can benefit from playing and reciprocating with the currently more trustworthy team. Investor behavior is actually generated by a novel computational model that parametrizes the teams' trust attitudes as the trade-off for the investor between potential losses and the gains expected from the players' joint choices. Occasionally, participants are shown an avatar and are asked to remember whether they have already played with the associated investor; this reminds them of their interaction. Results Preliminary results show that participants come to make good inferences about the teams' trust attitudes (which are not directly observable) and change their team preferences and reciprocal behaviors accordingly. Consequently, participants prefer to play with teams with greater trust attitudes and reciprocate according to their (putative) associated beliefs. In particular, participants reciprocate with higher back-transfers to an investor whose team they believe to have a greater trust attitude. Further, retrieval of a team with a greater trust attitude (at storage) increases participants' likelihood of choosing that team (at retrieval). The strength of these memory effects decayed linearly over trials. Conclusions This study provides important insights into memory effects on sequential, social decisions in interactive contexts, showing how individuals remember social interactions and how their retrieval biases subsequent decisions with other social partners.