The Acquisition and Use of Causal Structure Knowledge

Bibliographic Data

ID20031080
AuthorsBenjamin M Rottman (0000-0002-4718-3970, University of Pittsburgh, corresponding author), Michael Waldmann
EditorsMichael R Waldmann (0000-0002-8831-552X)
Year2017
Pages768
Publication date2017-05-10
Open AccessNo
TypeBOOK
VenueThe Oxford Handbook of Causal Reasoning (SOURCE_BOOK)
PublisherOxford University Press (PUBLISHER • GB)
DOI10.1093/oxfordhb/9780199399550.013.10
OpenAlexW2740541622
Open LibraryOL27416798M
ISBN9780199399550
LanguageEN
Citations received11

This chapter provides an introduction to how humans learn and reason about multiple causal relations connected together in a causal structure. The first half of the chapter focuses on how people learn causal structures. The main topics involve learning from observations versus interventions, learning temporal versus atemporal causal structures, and learning the parameters of a causal structure including individual cause-effect strengths and how multiple causes combine to produce an effect. The second half of the chapter focuses on how individuals reason about the causal structure, such as making predictions about one variable given knowledge about other variables, once the structure has been learned. Some of the most important topics involve reasoning about observations versus interventions, how well people reason compared to normative models, and whether causal structure beliefs bias reasoning. In both sections the author highlights open empirical and theoretical questions

Causal decision theory · Causal inference · Causal model · Causal reasoning · Causal structure · Causality (physics) · Cognition · Cognitive psychology · Cognitive science · Econometrics · Epistemology · Normative · Psychological intervention · Artificial Intelligence · Cognitive Science and Mapping · Computer Science · Mathematics · Philosophy · Psychology · Qualitative Comparative Analysis Research · Causation · Reasoning (Psychology)

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