Chapter

Two Proposals for Causal Grammars

Thomas L. Griffiths and Joshua B. Tenenbaum

in Causal Learning

Published in print April 2007 | ISBN: 9780195176803
Published online April 2010 | e-ISBN: 9780199958511 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195176803.003.0021

Series: Oxford Series in Cognitive Development

Two Proposals for Causal Grammars

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A causal theory can be thought of as a grammar that generates events, and that can be used to parse events to identify underlying causal structure. This chapter considers what the components of such a grammar might be — the analogues of syntactic categories and the rules that relate them in a linguistic grammar. It presents two proposals for causal grammars. The first asserts that the variables which describe events can be organized into causal categories, and allows relationships between those categories to be expressed. The second uses a probabilistic variant of first-order logic in order to describe the ontology and causal laws expressed in an intuitive theory. This chapter illustrates how both kinds of grammar can guide causal learning.

Keywords: causal learning; causal reasoning; intuitive theories; Bayesian inference; probabilistic models; generative grammar; first-order logic

Chapter.  13247 words.  Illustrated.

Subjects: Developmental Psychology

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