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强化神经网络统一理论无法模拟阻断效应。

Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

作者信息

Calvin Nicholas T, J McDowell J

机构信息

Emory University, Atlanta, Georgia.

Emory University, Atlanta, Georgia.

出版信息

Behav Processes. 2015 Nov;120:54-63. doi: 10.1016/j.beproc.2015.08.008. Epub 2015 Aug 28.

Abstract

For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed.

摘要

在过去20年里,强化统一理论(多纳霍等人,1993年)一直被用于开发计算机模拟程序,以评估其作为一种行为解释的合理性。强化统一理论指出,操作性学习和应答性学习是通过相同的神经机制发生的。作为评估该理论所预测的操作性行为的一个更大项目的一部分,本项目是基于强化统一理论的神经网络模型的首次复制。在复制这些神经网络模型的过程中,很明显,之前发表的一项发现,即这些网络模拟了阻断现象(多纳霍等人,1993年),是对数据的错误解读。我们表明,这些网络产生的明显阻断是由于它们无法对多种刺激产生相同的条件反应造成的假象。本文对通过模拟评估强化统一理论的零碎方法进行了批判,并讨论了替代方法。

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