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Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach

Description

This repository includes code and data necessary for reproducing the analyses presented in the attached pre-print of the paper "Augustat, N., Chuang, L.-C., Panitz, C., Stolz, C., Müller, E. M., Endres, D.: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach" to appear in the proceedings of CogSci 2022.

Metadata

Authors
Contributors
Supervisor:
Further Persons:
Dates
Issued: 2022-05-10
DOI
http://dx.doi.org/10.17192/fdr/89
Faculty
FB04:Psychologie
Language
eng
Data types
DatasetSoftware
Keywords
Psychology, Cognitive Science
DFG-subjects
110-01 Allgemeine, Kognitive und Mathematische Psychologie
DDC-Numbers
150
Funding
Funding Organisations:
Project Information:DFG SFB-TRR 289 "Treatment Expectation", project A07 (project number 422744262)
License
Creative Commons Attribution 4.0
URI
https://data.uni-marburg.de/handle/dataumr/159.6
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Files
Document
Type
Size
expectation_cogsci2022_v2.tar
1.21 GB
Augustat, Nick; Chuang, Li-Ching; Panitz, Christian; Stolz, Christopher: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach. 2022-05-10. DOI: http://dx.doi.org/10.17192/fdr/89.

Version History

Now showing 1 - 2 of 2
VersionDateSummary
6*
 2022-05-25 15:37:41
Pre-print updated to submitted paper
1
 2022-05-10 15:01:36
* Selected version