提出模拟与启发式双过程模型，解释人类物理直觉如何在不同计算成本下切换。
A simulation-heuristics dual-process model for intuitive physics
- 用模拟与启发式结合的双过程框架，模拟人类物理推理行为。
- 当模拟耗时超过阈值，启发式模型更准确预测人类判断。
- 适用于研究认知机制或人机交互中的直觉推理建模。
人类物理推理中心理模拟的作用广受认可，但其在不同模拟成本场景下的适用范围及边界尚不明确。通过倒水弹珠任务的人类实验，我们发现预测倾倒角度时存在两种不同的错误模式，区分依据是模拟时间长短。在简单场景中，心理模拟能准确捕捉人类判断；当模拟时间超过某一阈值时，线性启发式模型则更符合人类预测。基于此，我们提出双过程框架——模拟-启发式模型（SHM），该模型在短时模拟下使用模拟，当模拟代价过高时转为启发式。通过将此前被视为独立的方法整合为统一模型，SHM定量刻画了二者间的切换机制。该模型更精确地匹配人类行为，并在多种场景中保持一致的预测性能，深化了对直觉物理推理适应性的理解。
原文摘要 · Abstract (English)
The role of mental simulation in human physical reasoning is widely acknowledged, but whether it is employed across scenarios with varying simulation costs and where its boundary lies remains unclear. Using a pouring-marble task, our human study revealed two distinct error patterns when predicting pouring angles, differentiated by simulation time. While mental simulation accurately captured human judgments in simpler scenarios, a linear heuristic model better matched human predictions when simulation time exceeded a certain boundary. Motivated by these observations, we propose a dual-process framework, Simulation-Heuristics Model (SHM), where intuitive physics employs simulation for short-time simulation but switches to heuristics when simulation becomes costly. By integrating computational methods previously viewed as separate into a unified model, SHM quantitatively captures their switching mechanism. The SHM aligns more precisely with human behavior and demonstrates consistent predictive performance across diverse scenarios, advancing our understanding of the adaptive nature of intuitive physical reasoning.
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