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  Asymmetric reinforcement learning facilitates human inference of transitive relations

Ciranka, S., Linde-Domingo, J., Padezhki, I., Wicharz, C., Wu, C. M., & Spitzer, B. (2022). Asymmetric reinforcement learning facilitates human inference of transitive relations. Nature Human Behaviour, 6, 555-564. doi:10.1038/s41562-021-01263-w.

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 Creators:
Ciranka, Simon1, 2, Author           
Linde-Domingo, Juan1, Author           
Padezhki, Ivan1, Author           
Wicharz, Clara1, Author           
Wu, Charley M.1, Author           
Spitzer, Bernhard1, 2, 3, Author           
Affiliations:
1Center for Adaptive Rationality, Max Planck Institute for Human Development, Max Planck Society, ou_2074286              
2Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK, Max Planck Institute for Human Development, Max Planck Society, Lentzeallee 94, D-14195 Berlin, DE; Russell Square House, 10-12 Russell Square, London, WC1B 5EH, UK, ou_2205641              
3Research Group Adaptive Memory and Decision Making, Max Planck Institute for Human Development, Max Planck Society, Lentzeallee 94, D-14195 Berlin, DE, ou_3357611              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Published in print
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41562-021-01263-w
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Title: Nature Human Behaviour
Source Genre: Journal
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Pages: - Volume / Issue: 6 Sequence Number: - Start / End Page: 555 - 564 Identifier: -