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儿童错误信念推理的贝叶斯框架:理论论与模拟论的理性整合

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

作者信息

Asakura Nobuhiko, Inui Toshio

机构信息

Department of Psychology, Otemon Gakuin University Osaka, Japan.

出版信息

Front Psychol. 2016 Dec 27;7:2019. doi: 10.3389/fpsyg.2016.02019. eCollection 2016.

Abstract

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

摘要

为了解释儿童心理理论(ToM)的发展,人们提出了两种明显相互矛盾的理论:理论论和模拟论。我们提出了一个贝叶斯框架,该框架合理地整合了这两种理论用于错误信念推理。这个框架利用两个内部模型来预测他人的信念状态:一个是关于自我的,另一个是关于他人的。这些内部模型分别负责基于模拟的推理和基于理论的推理。该框架还考虑了一个发展性ToM量表的实证研究(例如,韦尔曼和刘,2004):各种心理状态理解在达到错误信念理解之前的发展进程。通过将内部模型及其相互作用表示为一个因果贝叶斯网络,我们将儿童错误信念推理模型形式化为贝叶斯网络上的概率计算。这个模型以概率方式权衡并结合这两个内部模型,并将儿童的错误信念能力预测为他们早期发展的理解不同信念和知识获取心理概念能力的乘积效应。具体来说,该模型预测,儿童在错误信念任务上的正确反应比例可以近似为他们在不同信念和知识获取任务上正确比例的乘积。为了验证这一预测,我们表明我们的模型与学龄前儿童的各种ToM量表数据拟合良好。我们讨论了我们的模型对于更深入理解儿童ToM能力发展进程的意义和扩展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b314/5186777/2f406e0bdb98/fpsyg-07-02019-g0001.jpg

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