The psychology of computer vision

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Unmasking Clever Hans predictors and assessing what machines really learn (2019, background): “Commonly discussed ingredients to make learning machines act more human-like are, e.g. compositionality, causality, learning to learn 39 – 41 , and also an ef ﬁ cient usage of prior knowledge or invariance structure (see e.g. 44 ).”
Constructing inferences during narrative text comprehension. (1994, unknown): “Mandler, 1984; Rumelhart & Ortony, 1977), scripts (Bower, Black, & Turner, 1979; Schank & Abelson, 1977), frames (Minsky, 1975), stereotypes (Wyer & Gordon, 1984), and other structured packets of generic knowledge.”
Interaction Networks for Learning about Objects, Relations and Physics (2016, background): “Previous AI work on physical reasoning explored commonsense knowledge, qualitative representa62 tions, and simulation techniques for approximating physical prediction and inference [28, 9, 6].”
The status of the minimum principle in the theoretical analysis of visual perception. (1985, background): “Minskys (1975) frame theory is one such alternative.”