语义记忆搜索的基于代理模型:解开认知控制和语义空间组织
Diego Morales1, Sergio E Chaigneau2, Enrique Canessa1
1Faculty of Engineering and Science, Universidad Adolfo Ibáñez.
Cognitive science
|December 24, 2025
概括
人类语义记忆检索涉及适应性搜索策略,而不仅仅是随机或固定的过程. 区域限制搜索 (ARS) 模型更好地解释了人类在各种语义结构中的语言流模式.
科学领域:
- 认知科学 认知科学
- 计算神经科学是一种神经科学.
- 心理学 心理学 心理学
背景情况:
- 语言流利任务显示语义聚类和切换.
- 现有的模型往往忽视了搜索策略和语义记忆结构之间的相互作用.
- 战略与随机搜索模型的优越性仍在争论中.
研究的目的:
- 开发和验证一种新的基于代理的区域限制搜索 (ARS) 模型,用于语义记忆检索.
- 在不同的语义结构下比较ARS与Lévy Walk (LW) 和Random Walk (RW) 模型.
- 研究不同搜索机制如何与语义组织相互作用.
主要方法:
- 开发了一个基于ARS代理的模型,具有增量决策和本地信息使用.
- 系统地改变语义结构参数 (集群,密度,分散).
- 评估了对50名参与者的模型性能,使用聚类,切换和时间指标.
主要成果:
- 在适度集群的语义结构中,ARS表现出色.
- 在稀疏结构中LW表现最好,在密集结构中RW表现最好,但RW偏离了人类数据.
- 当语义密度受到限制时,ARS在各种配置中展示了类似人类的性能,而不是LW和RW.
结论:
- 类似人类的语义记忆检索需要动态的,自适应的搜索策略.
- 没有一个单一的随机过程 (LW,RW) 可以普遍解释所有语义结构的检索.
- 区域限制搜索 (ARS) 模型提供了一个更灵活和更类似于人类的语义记忆检索.
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