Chapter

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: http://dx.doi.org/10.1093/acprof:oso/9780195176803.003.0015

Series: Oxford Series in Cognitive Development

Learning the Structure of Deterministic Systems

Show Summary Details

Preview

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

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.