Silveira Paulo Sergio Panse, de Oliveira Siqueira José, Bernardy João Lucas, Santiago Jessica, Meneses Thiago Cersosimo, Portela Bianca Sanches, Benvenuti Marcelo Frota
Department of Pathology, University of São Paulo, Medical School, São Paulo, Brazil.
Department of Legal Medicine, Medical Ethics, Work and Social Medicine, University of São Paulo, Medical School, São Paulo, Brazil.
J Exp Anal Behav. 2023 Mar;119(2):324-336. doi: 10.1002/jeab.826. Epub 2023 Feb 2.
We present the mathematical description of feedback functions of variable interval and variable differential reinforcement of low rates as functions of schedule size only. These results were obtained using an R script named Beak, which was built to simulate rates of behavior interacting with simple schedules of reinforcement. Using Beak, we have simulated data that allow an assessment of different reinforcement feedback functions. This was made with unparalleled precision, as simulations provide huge samples of data and, more importantly, simulated behavior is not changed by the reinforcement it produces. Therefore, we can vary response rates systematically. We've compared different reinforcement feedback functions for random interval schedules, using the following criteria: meaning, precision, parsimony, and generality. Our results indicate that the best feedback function for the random interval schedule was published by Baum (1981). We also propose that the model used by Killeen (1975) is a viable feedback function for the random differential reinforcement of low rates schedule. We argue that Beak paves the way for greater understanding of schedules of reinforcement, addressing still open questions about quantitative features of simple schedules. Also, Beak could guide future experiments that use schedules as theoretical and methodological tools.
我们仅将可变时距和低速率可变比率强化的反馈函数作为时间表规模的函数进行数学描述。这些结果是使用一个名为Beak的R脚本获得的，该脚本用于模拟与简单强化时间表相互作用的行为速率。使用Beak，我们模拟了能够评估不同强化反馈函数的数据。这是以无与伦比的精度完成的，因为模拟提供了大量的数据样本，更重要的是，模拟行为不会因其产生的强化而改变。因此，我们可以系统地改变反应速率。我们使用以下标准比较了随机时距时间表的不同强化反馈函数：意义、精度、简约性和普遍性。我们的结果表明，随机时距时间表的最佳反馈函数由鲍姆（1981年）发表。我们还提出，基林（1975年）使用的模型是低速率随机比率强化时间表的可行反馈函数。我们认为，Beak为更深入理解强化时间表铺平了道路，解决了关于简单时间表定量特征的悬而未决的问题。此外，Beak可以指导未来将时间表用作理论和方法工具的实验。
