一般化跨维度模型适用于条件时间歧视
Michael Davison1, Sarah Cowie1
1The University of Auckland, Aotearoa, New Zealand.
Journal of the experimental analysis of behavior
|April 17, 2024
概括
最近的定量模型可以解释条件歧视任务中的选择行为. 然而,由于强化器控制的不同,一个实验的模型参数无法预测另一个实验,这凸显了进一步研究的必要性.
科学领域:
- 行为心理学 行为心理学
- 定量建模 定量建模 定量建模
- 动物认知动物的认知能力.
背景情况:
- 最近的定量模型整合了刺激和加强控制.
- 了解条件歧视中的选择行为至关重要.
研究的目的:
- 测试最近的定量模型是否可以解释条件歧视下的选择行为.
- 调查刺激的影响,并加强对选择的控制.
主要方法:
- 两项实验利用停电时间作为条件刺激来信号食物的可用性.
- 停电时间的分布在各种设置和条件之间各不相同.
- 应用了更新的泛化跨维度模型来分析选择数据.
主要成果:
- 在实验1中,该模型准确地描述了不同时间段的选择变化.
- 实验1的模型参数没有预测实验2的选择.
- 尽管参数预测失败,该模型仍然很好地适应了实验2的数据.
结论:
- 一般化跨维度模型扩展到条件歧视程序.
- 强化器位置的差异控制在实验之间有所不同,影响了预测准确性.
- 需要进一步的研究,以阐明不同强化器控制的原因.
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