Modeling VI and VDRL feedback functions: searching normative rules through computational simulation
Abstract
In this paper, we present a R script named Beak, built to simulate rates of behavior interacting with schedules of reinforcement. Using Beak, we've simulated data that allows an assessment of different reinforcement feedback functions (RFF). This was made with unparalleled precision, since simulations provide huge samples of data and, more importantly, simulated behavior isn't changed by the reinforcement it produces. Therefore, we can vary it systematically. We've compared different RFF for RI schedules, using as criteria: meaning, precision, parsimony and generality. Our results indicate that the best feedback function for the RI schedule was published by Baum (1981). We also propose that the model used by Killeen (1975) is a viable feedback function for the RDRL schedule. We argue that Beak paves the way for greater understanding of schedules of reinforcement, addressing still open questions about quantitative features of schedules. Also, they could guide future experiments that use schedules as theoretical and methodological tools.
Cite
@article{arxiv.2111.13943,
title = {Modeling VI and VDRL feedback functions: searching normative rules through computational simulation},
author = {Paulo Sergio Panse Silveira and Jose de Oliveira Siqueira and Joao Lucas Bernardy and Jessica Santiago and Thiago Cersosimo Meneses and Bianca Sanches Portela and Marcelo Frota Benvenuti},
journal= {arXiv preprint arXiv:2111.13943},
year = {2022}
}
Comments
This is a revised version of the manuscript submitted for consideration for publication in the Journal of the Experimental Analysis of Behavior (JEAB) in July 6th, 2022. Supplemental material is available under SourceForge at https://sourceforge.net/projects/simpleschedules/