Partial mental simulation explains fallacies in physical reasoning
Partial mental simulation explains fallacies in physical reasoning
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DOI：
10.1080/02643294.2022.2083950
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发表时间：
2022-06-04
影响因子：
3.4
通讯作者：
Ullman, Tomer D.
中科院分区：
文献类型：
--
作者：
Bass, Ilona;Smith, Kevin A.;Ullman, Tomer D.
人们可以直观，高效，准确地推进日常的身体事件。最近的报道表明，人们使用精神模拟做出如此直观的身体判断。但是心理模拟模型在计算上昂贵。在维持计算障碍的同时，物理推理如何相对准确？我们建议人们利用部分模拟，在心理上向前迈进，只有世界各地的部分被认为是相关的。我们提出了一个新型的部分仿真模型，并对物理结合谬误进行了测试，最近观察到的现象[Ludwin-Peery等。 （2020）。损坏的物理：直觉物理推理中的结合效果。心理科学，37（12），1602-1611。 https://doi.org/10.1177/0956797620957610]，对完整模拟模型构成了挑战。我们在模型的预测与人类绩效之间发现了一系列场景之间的良好拟合，这些场景基于Ludwin-Peery等人的使用。 [（2020）。损坏的物理：直觉物理推理中的结合效果。心理科学，31（12），1602-1611。 haps：//doi.org/10.1177/0956797620957610]，定量和定性地考虑到最佳性能的偏差。我们的结果更一般地表明了我们如何分配认知资源以有效地表示和模拟物理场景。
People can reason intuitively, efficiently, and accurately about everyday physical events. Recent accounts suggest that people use mental simulation to make such intuitive physical judgments. But mental simulation models are computationally expensive; how is physical reasoning relatively accurate, while maintaining computational tractability? We suggest that people make use of partial simulation, mentally moving forward in time only parts of the world deemed relevant. We propose a novel partial simulation model, and test it on the physical conjunction fallacy, a recently observed phenomenon [Ludwin-Peery et al. (2020). Broken physics: A conjunction-fallacy effect in intuitive physical reasoning. Psychological Science, 37(12), 1602-1611. https://doi.org/10.1177/0956797620957610] that poses a challenge for full simulation models. We find an excellent fit between our model's predictions and human performance on a set of scenarios that build on and extend those used by Ludwin-Peery et al. [(2020). Broken physics: A conjunction-fallacy effect in intuitive physical reasoning. Psychological Science, 31(12), 1602-1611. haps://doi.org/10.1177/0956797620957610], quantitatively and qualitatively accounting for deviations from optimal performance. Our results suggest more generally how we allocate cognitive resources to efficiently represent and simulate physical scenes.