| Literature DB >> 28711322 |
James R Kubricht1, Keith J Holyoak2, Hongjing Lu2.
Abstract
Early research in the field of intuitive physics provided extensive evidence that humans succumb to common misconceptions and biases when predicting, judging, and explaining activity in the physical world. Recent work has demonstrated that, across a diverse range of situations, some biases can be explained by the application of normative physical principles to noisy perceptual inputs. However, it remains unclear how knowledge of physical principles is learned, represented, and applied to novel situations. In this review we discuss theoretical advances from heuristic models to knowledge-based, probabilistic simulation models, as well as recent deep-learning models. We also consider how recent work may be reconciled with earlier findings that favored heuristic models.Entities:
Keywords: computation; intuitive physics; mental simulation; misconceptions; probabilistic simulation
Mesh:
Year: 2017 PMID: 28711322 DOI: 10.1016/j.tics.2017.06.002
Source DB: PubMed Journal: Trends Cogn Sci ISSN: 1364-6613 Impact factor: 20.229