Reinforcement Learning Tools for Two-Alternative Forced Choice Tasks

Tools for building Rescorla-Wagner Models for Two-Alternative Forced Choice tasks, commonly employed in psychological research. Most concepts and ideas within this R package are referenced from Sutton and Barto (2018) . The package allows for the intuitive definition of RL models using simple if-else statements and three basic models built into this R package are referenced from Niv et al. (2012) . Our approach to constructing and evaluating these computational models is informed by the guidelines proposed in Wilson & Collins (2019) . Example datasets included with the package are sourced from the work of Mason et al. (2024) .


Reference manual

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install.packages("binaryRL")

0.9.9 by YuKi, 9 months ago


https://yuki-961004.github.io/binaryRL/


Report a bug at https://github.com/yuki-961004/binaryRL/issues


Browse source code at https://github.com/cran/binaryRL


Authors: YuKi [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, compiler, future, doFuture, foreach, doRNG, progressr

Suggests stats, GenSA, GA, DEoptim, pso, mlrMBO, mlr, ParamHelpers, smoof, lhs, DiceKriging, rgenoud, cmaes, nloptr

Linking to Rcpp


See at CRAN