Learning the Structure of Deterministic Systems

Clark Glymour

in Causal Learning

Published in print April 2007 | ISBN: 9780195176803
Published online April 2010 | e-ISBN: 9780199958511 | DOI:

Series: Oxford Series in Cognitive Development

Learning the Structure of Deterministic Systems

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Consider a system represented by a directed acyclic graph with variables as vertices in which represented variable is a deterministic function of its parents. Most engineered systems without feedback instantiate such structures, and so, at least to appearances, do many macroscopic, natural inanimate systems. Learning the graphical representation of causal structure without experimental controls is especially difficult for such systems, because while the Markov condition holds, faithfulness does not. This chapter illustrates the problem and describes a heuristic (and not very satisfactory) learning procedure.

Keywords: determinism; learning; causality; Markov; faithfulness

Chapter.  4821 words.  Illustrated.

Subjects: Developmental Psychology

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