用信息论解释自闭症对一致性的执着，揭示其背后的心理机制。
An entropic explanation of insistence on sameness in autism
- 将自闭症的坚持一致性视为降低环境不确定性的一种策略。
- 提出熵度量公式，量化惊讶、焦虑与舒适区等心理状态。
- 可指导康复训练设计，甚至用于开发智能照护机器人。
本文提出一种基于信息论的框架，试图将自闭症中对一致性的执着理解为个体减少意外和不确定性的普遍行为模式。该框架将自闭症重新定义为认知功能受限于环境有形属性的辨别、记忆与预测能力。通过分析随机刺激序列R与记忆M之间的条件熵 $H(R|M)$ 与 $H(M|R)$，构建熵度量 $D_H(R, M) = H(R|M) + H(M|R)$，反映个体感知中的惊讶与不确定性。推导表明，最小化该度量可通过学习并存储新信息或限制外界输入以匹配已有记忆实现；而自闭症的坚持一致性正是后者的体现。该框架可定量刻画惊讶、焦虑、感官过载、固执、精确性偏差等概念，并为康复训练提供优化算法指导，甚至可用于开发具备自主护理功能的机器人系统。此外，其有效性可通过类图灵测试方式验证，无需直接实验于自闭症人群。若获证实，将为提升自闭症患者日常生活自理能力提供理论基础与设计规范。
原文摘要 · Abstract (English)
An information theory-based framework is proposed in attempt to explain insistence on sameness in autism as an instance of a general behavior pattern in which an individual tries to reduce surprise and uncertainty. It offers a new definition of autism as an impairment in which cognitive functions are restricted to discrimination, memorization and prediction of tangible properties of the environment. An analogy between insistence on sameness and constrained minimization of the entropy metric is observed and examined for a set of assumptions that describe cognitive limitations of a person with autism. The metric is given by the formula $D_H(R, M) = H(R|M) + H(M|R)$, where $R$ represents sequences of random stimuli, $M$ is a memory that stores and retrieves them, and where $H(.|.)$ denotes their conditional entropies interpreted as surprise and uncertainty, respectively. It is first inferred that to minimize the metric an individual can learn about $R$ (and store that knowledge in $M$) or can restrict $R$ to the already known $M$. Then, it is concluded that insistence on sameness is a manifestation of the latter. Moreover, it is shown that the proposed framework: (1) Helps to quantify the concepts of surprise, uncertainty, sensory overload and deprivation, anxiety, comfort zone, disappointment, disorientation, pedantry, rigidness, observance or aberrant precision. (2) Leads to a list of guidelines for learning therapies and daily care routines, and allows them to be defined as optimization algorithms and implemented as programs for robotic live-in caregivers. (3) Can be validated with the help of a Turing test-like approach that requires no experiments involving individuals with autism. The framework-if positively validated-will provide formal foundations and design guidelines for therapies aimed at improving self-reliance of individuals with autism in basic activities of daily living.
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