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Revisiting peak shift on an artificial dimension: Effects of stimulus variability on generalisation

机译:在人工维思上重新审查峰值转变:刺激变异性对泛化的影响

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One of Mackintosh's many contributions to the comparative psychology of associative learning was in developing the distinction between the mental processes responsible for learning about features and learning about relations. His research on discrimination learning and generalisation served to highlight differences and commonalities in learning mechanisms across species and paradigms. In one such example, Wills and Mackintosh trained both pigeons and humans to discriminate between two categories of complex patterns comprising overlapping sets of abstract visual features. They demonstrated that pigeons and humans produced similar peak-shifted generalisation gradients when the proportion of shared features was systemically varied across a set of transfer stimuli, providing support for an elemental feature-based analysis of discrimination and generalisation. Here, we report a series of experiments inspired by this work, investigating the processes involved in post-discrimination generalisation in human category learning. We investigate how post-discrimination generalisation is affected by variability in the spatial arrangement and probability of occurrence of the visual features and develop an associative learning model that builds on Mackintosh's theoretical approach to elemental associative learning.
机译:MackintoSh是对联合学习的比较心理学的许多贡献在发展责任学习特征和学习关系的心理过程之间的区别。他对歧视学习和泛化的研究旨在突出物种和范例突出学习机制的差异和共性。在一个这样的示例中,威尔斯和麦克风培训鸽子和人类培训,以区分两类复杂模式,包括重叠的抽象视觉特征。他们证明,当共享特征的比例在一组转移刺激上系统地变化时,鸽子和人类产生了类似的峰值偏移梯度,从而提供了对基于元素特征的辨别和泛化分析的支持。在这里,我们报告了一系列受到这项工作的实验,调查人类类别学习中歧视后概括的过程。我们调查歧视后概括受到空间安排的可变性以及视觉特征的发生概率的影响,以及开发一个基于Mackintosh的基本联想学习的理论方法的关联学习模型。

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