ArticleJournal of experimental psychology. General2023
The role of memory in counterfactual valuation.
Article in Journal of experimental psychology. General, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- How working memory and reinforcement learning interact when avoiding punishment and pursuing reward concurrently.Journal of experimental psychology. General · 2025Article
- Cognitive Graphs: Representational Substrates for Planning.Decision (Washington, D.C.) · 2024Article
- Modulating social learning-induced evaluation updating during human sleep.NPJ science of learning · 2024Article
- Computational mechanisms underlying latent value updating of unchosen actions.Science advances · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
Value-based decisions are often guided by past experience. If a choice led to a good outcome, we are more likely to repeat it. This basic idea is well-captured by reinforcement-learning models. However, open questions remain about how we assign value to options we did not choose and which we therefore never had the chance to learn about directly. One solution to this problem is proposed by policy gradient reinforcement-learning models; these do not require direct learning of value, instead optimizing choices according to a behavioral policy. For example, a logistic policy predicts that if a chosen option was rewarded, the unchosen option would be deemed less desirable. Here, we test the relevance of these models to human behavior and explore the role of memory in this phenomenon. We hypothesize that a policy may emerge from an associative memory trace formed during deliberation between choice options. In a preregistered study (
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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.