用模板程序建模人类如何识别序列中的层级重复结构
A Computational Cognitive Model for Processing Repetitions of Hierarchical Relations
- 基于加权推演系统构建模板程序，编码递归重复计算
- 在音乐和动作规划数据中成功识别短序列的层级重复模式
- 为理解人类模式识别的心理机制提供新计算视角
模式是人类认知的基础，使我们能在不同领域中识别结构与规律。本文聚焦于结构重复：由序列数据中层级关系的重复所形成的模式，提出一种人类检测与理解此类结构重复的候选计算模型。该模型基于加权推演系统，将给定序列的最小生成过程表示为模板程序（Template program），这是一种在上下文无关文法基础上引入重复组合子的形式化表达。这种表示能以递归方式高效编码子计算的重复。作为概念验证，我们在音乐和动作规划的短序列上展示了模型的表达能力。该模型为理解人类模式识别背后的认知表征与机制提供了更广泛的洞见。
原文摘要 · Abstract (English)
Patterns are fundamental to human cognition, enabling the recognition of structure and regularity across diverse domains. In this work, we focus on structural repeats, patterns that arise from the repetition of hierarchical relations within sequential data, and develop a candidate computational model of how humans detect and understand such structural repeats. Based on a weighted deduction system, our model infers the minimal generative process of a given sequence in the form of a Template program, a formalism that enriches the context-free grammar with repetition combinators. Such representation efficiently encodes the repetition of sub-computations in a recursive manner. As a proof of concept, we demonstrate the expressiveness of our model on short sequences from music and action planning. The proposed model offers broader insights into the mental representations and cognitive mechanisms underlying human pattern recognition.
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