通过程序生成来探索人类计划的等级结构.
Carlos G Correa1, Sophia Sanborn2, Mark K Ho3
1Princeton Neuroscience Institute, Princeton University, USA.
Cognition
|December 1, 2024
概括
人类按层次计划行动,以更短的程序平衡更少的步骤. 然而,它们也显示出对重复使用动作序列的偏好,这种因素在现有模型中无法完全解释.
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.
- 人与计算机的交互
背景情况:
- 人类行为通常被概念化为等级,抽象的行为分解为具体的行为.
- 推断行为层次是具有挑战性的,因为作为简单的序列的行动测量.
研究的目的:
- 研究人类如何形成层次结构的计划.
- 在层次规划中测试实用性最大化和最小描述长度 (MDL) 的原则.
- 开发一个模型来解释人类对行动的偏好,在规划中重复使用.
主要方法:
- 使用具有明确层次结构的编程语言的实验范式.
- 参与者创建程序来生成动作序列.
- 分析程序指标,包括动作数和程序长度 (MDL).
主要成果:
- 人类既考虑效用最大化 (较少的行动),也考虑MDL (较短的程序).
- 现有的模型无法预测观察到的人类对程序重复使用的偏好.
- 一个包含语法诱导的新型生成模型解释了重复使用的偏好.
结论:
- 人类的层次规划不仅仅涉及到将行动或程序长度最小化.
- 对重复使用动作序列的偏好是人类层次规划的一个关键原则.
- 提出的生成模型提供了更准确的预测人类的规划行为.
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