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Inductive reasoning 2.0
Author(s) -
Hayes Brett K.,
Heit Evan
Publication year - 2017
Publication title -
wiley interdisciplinary reviews: cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.526
H-Index - 49
eISSN - 1939-5086
pISSN - 1939-5078
DOI - 10.1002/wcs.1459
Subject(s) - inductive reasoning , generalization , computer science , deductive reasoning , connectionism , artificial intelligence , identification (biology) , field (mathematics) , cognitive science , machine learning , management science , psychology , epistemology , artificial neural network , mathematics , philosophy , botany , pure mathematics , economics , biology
Inductive reasoning entails using existing knowledge to make predictions about novel cases. The first part of this review summarizes key inductive phenomena and critically evaluates theories of induction. We highlight recent theoretical advances, with a special emphasis on the structured statistical approach, the importance of sampling assumptions in Bayesian models, and connectionist modeling. A number of new research directions in this field are identified including comparisons of inductive and deductive reasoning, the identification of common core processes in induction and memory tasks and induction involving category uncertainty. The implications of induction research for areas as diverse as complex decision‐making and fear generalization are discussed. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Learning