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• W2901507688 abstract "Significance In the present study, we applied reinforcement learning models that are not classically used in experimental economics to a multistep exchange task of the emergence of money derived from a classic search-theoretic paradigm for the emergence of money. This method allowed us to highlight the importance of counterfactual feedback processing of opportunity costs in the learning process of speculative use of money and the predictive power of reinforcement learning models for multistep economic tasks. Those results constitute a step toward understanding the learning processes at work in multistep economic decision-making and the cognitive microfoundations of the use of money." @default.
• W2901507688 created "2018-11-29" @default.
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• W2901507688 date "2018-11-15" @default.
• W2901507688 modified "2023-10-04" @default.
• W2901507688 title "Contrasting temporal difference and opportunity cost reinforcement learning in an empirical money-emergence paradigm" @default.
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• W2901507688 doi "https://doi.org/10.1073/pnas.1813197115" @default.
• W2901507688 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6298096" @default.
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