将地理判断分解为空间,时间和语言组件
Daniele Gatti1, Giorgia Anceresi2, Marco Marelli3,4
1Department of Brain and Behavioral Sciences, University of Pavia, Piazza Botta 6, 27100, Pavia, Italy. daniele.gatti@unipv.it.
Psychological research
|June 5, 2024
概括
人类使用空间和语言信息在脑海中探索大型地图. 来自人工智能模型的语言数据显著有助于距离判断,补充空间记忆在形成认知图的过程中.
科学领域:
- 认知心理学 认知心理学
- 神经科学是一个神经科学.
- 人工智能的人工智能
背景情况:
- 人类对大规模环境的空间认知通常假定依赖于直接的感知体验.
- 非空间信息的作用,如时间和语言数据,在形成认知图的作用是不太了解.
研究的目的:
- 调查时间和语言信息是否影响人类对大规模地图的心理探索.
- 确定语言信息是否可以解释人类在远程判断任务中的表现,超出空间信息范围.
主要方法:
- 使用意大利城市之间的最低火车行程时间量化的时间距离.
- 从自然语言中使用基于人工智能的分布式语义模型检索语言距离.
- 进行行为实验,以评估城市之间的距离判断.
主要成果:
- 时间和语言距离准确地反映了实际的地理距离.
- 语言信息显著改善了距离判断性能,即使考虑了空间信息.
- 时间信息在远程判断任务中没有显示相关性.
结论:
- 对于大规模环境的人类认知地图的形成集成了感知和非空间信息.
- 由人工智能模型促进的语言处理在空间认知中起着至关重要的作用.
- 认知地图的开发可能涉及空间和非空间学习原则之间的相互作用.
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