ArticlePLoS biology2020
The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning.
Article in PLoS biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 68 citations in OpenAlex.
- Social learning dynamically shapes moral decision-making by biasing subjective valuation.PLoS biology · 2026Article
- Reward and Imitation in Social Conformity.Brain and behavior · 2026Article
- Adaptive yet suboptimal integration of advice in decision-making.Communications psychology · 2026Article
- Social information creates self-fulfilling prophecies in judgments of pain, vicarious pain, and cognitive effort.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Social learning and exploration-exploitation dilemma in decision-making.Frontiers in neural circuits · 2026Review
- On the origin of the reward function: Exploring the role of conditioned reinforcement and social learning.Psychonomic bulletin & review · 2025Review
- How social learning enhances-or undermines-efficiency and flexibility in collective decision-making under uncertainty.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Whom do we prefer to learn from in observational reinforcement learning?PLoS computational biology · 2025Article
- Feature-based reward learning shapes human social learning strategies.Nature human behaviour · 2025Article
- How the self-concept structures social role learning: insights from computational models.Royal Society open science · 2025Article
- Neural correlates of Bayesian social belief updating in the medial prefrontal cortex.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- The Effects of Teacher Rewards and Their Types on Preschool Children's Selective Trust.Behavioral sciences (Basel, Switzerland) · 2025Article
- Adaptive mechanisms of social and asocial learning in immersive collective foraging.Nature communications · 2025Article
- Self-utility distance as a computational approach to understanding self-concept clarity.Communications psychology · 2025Article
- Effects of described demonstrator ability on brain and behavior when learning from others.NPJ science of learning · 2025Article
- When to stop social learning from a predecessor in an information-foraging task.Evolutionary human sciences · 2025Article
- Experience and advice consequences shape information sharing strategies.Communications psychology · 2024Article
- Causal involvement of dorsomedial prefrontal cortex in learning the predictability of observable actions.Nature communications · 2024Article
- Humans flexibly integrate social information despite interindividual differences in reward.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Transmission of social bias through observational learning.Science advances · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While there is no doubt that social signals affect human reinforcement learning, there is still no consensus about how this process is computationally implemented. To address this issue, we compared three psychologically plausible hypotheses about the algorithmic implementation of imitation in reinforcement learning. The first hypothesis, decision biasing (DB), postulates that imitation consists in transiently biasing the learner's action selection without affecting their value function. According to the second hypothesis, model-based imitation (MB), the learner infers the demonstrator's value function through inverse reinforcement learning and uses it to bias action selection. Finally, according to the third hypothesis, value shaping (VS), the demonstrator's actions directly affect the learner's value function. We tested these three hypotheses in 2 experiments (N = 24 and N = 44) featuring a new variant of a social reinforcement learning task. We show through model comparison and model simulation that VS provides the best explanation of learner's behavior. Results replicated in a third independent experiment featuring a larger cohort and a different design (N = 302). In our experiments, we also manipulated the quality of the demonstrators' choices and found that learners were able to adapt their imitation rate, so that only skilled demonstrators were imitated. We proposed and tested an efficient meta-learning process to account for this effect, where imitation is regulated by the agreement between the learner and the demonstrator. In sum, our findings provide new insights and perspectives on the computational mechanisms underlying adaptive imitation in human reinforcement learning.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.