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惩罚与动态选择:直接抑制模型的评估

Punishment and dynamic choice: Assessment of the direct-suppression model.

作者信息

Fontes Rafaela M, Shahan Timothy A

机构信息

Utah State University, Logan, UT, USA.

出版信息

J Exp Anal Behav. 2025 Mar;123(2):158-175. doi: 10.1002/jeab.4237. Epub 2025 Jan 30.

Abstract

The effects of punishment rate on response allocation were investigated using a choice procedure where relative reinforcement rates changed rapidly within session. Predictions from a modified version of the direct-suppression model were tested in two separate experiments. In both experiments, sessions were composed of seven unsignaled components, each programming a different reinforcement ratio. In Experiment 1, equal punishment rates were superimposed on the schedule of reinforcement for both responses and absolute punishment rates increased across blocks of sessions. Punishment increased preference for the richer schedule of reinforcement, but the degree of the preference shift was not a function of absolute punishment rates. In Experiment 2, unequal punishment rates were superimposed on the schedules of reinforcement for both responses and relative punishment rates changed across blocks of sessions. Response allocation shifted away from the richer punishment schedule creating a bias toward the option associated with less frequent punishment. The results from both experiments challenged the predictions of the direct-suppression model. Furthermore, fits of the generalized matching law to the data indicated that superimposition of equal or unequal punishment schedules on responses maintained by unequal reinforcement schedules differentially affect the values of sensitivity and bias.

摘要

使用一种选择程序来研究惩罚率对反应分配的影响,在该程序中,相对强化率在实验过程中迅速变化。在两个独立的实验中测试了直接抑制模型修改版本的预测。在两个实验中,实验过程均由七个无信号成分组成,每个成分设定不同的强化比率。在实验1中,对两种反应的强化程序叠加了相等的惩罚率,并且绝对惩罚率在各实验阶段组中增加。惩罚增加了对更丰富强化程序的偏好,但偏好转移的程度不是绝对惩罚率的函数。在实验2中,对两种反应的强化程序叠加了不相等的惩罚率,并且相对惩罚率在各实验阶段组中变化。反应分配从更丰富的惩罚程序转移,产生了对与较少频繁惩罚相关选项的偏向。两个实验的结果都挑战了直接抑制模型的预测。此外,广义匹配定律对数据的拟合表明,在由不相等强化程序维持的反应上叠加相等或不相等的惩罚程序会对敏感性和偏向的值产生不同影响。

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