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binaryRL  

Reinforcement Learning Tools for Two-Alternative Forced Choice Tasks
View on CRAN: Click here


Download and install binaryRL package within the R console
Install from CRAN:
install.packages("binaryRL")

Install from Github:
library("remotes")
install_github("cran/binaryRL")

Install by package version:
library("remotes")
install_version("binaryRL", "0.9.9")



Attach the package and use:
library("binaryRL")
Maintained by
YuKi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-05-13
Latest Update: 2025-07-08
Description:
Tools for building reinforcement learning (RL) models specifically tailored for Two-Alternative Forced Choice (TAFC) tasks, commonly employed in psychological research. These models build upon the foundational principles of model-free reinforcement learning detailed in Sutton and Barto (1998) <ISBN:0262039249>. The package allows for the intuitive definition of RL models using simple if-else statements. Our approach to constructing and evaluating these computational models is informed by the guidelines proposed in Wilson & Collins (2019) <doi:10.7554/eLife.49547>. Example datasets included with the package are sourced from the work of Mason et al. (2024) <doi:10.3758/s13423-023-02415-x>.
How to cite:
YuKi (2025). binaryRL: Reinforcement Learning Tools for Two-Alternative Forced Choice Tasks. R package version 0.9.9, https://cran.r-project.org/web/packages/binaryRL. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:21), 0.8.0 (2025-05-13 10:10), 0.8.3 (2025-05-23 13:52), 0.8.7 (2025-06-10 14:10), 0.8.9 (2025-06-15 11:10), 0.9.0 (2025-07-08 15:20), 0.9.7 (2025-08-20 01:50), 0.9.8 (2025-10-28 12:00)
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Complete documentation for binaryRL
Functions, R codes and Examples using the binaryRL R package
Full binaryRL package functions and examples
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