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Minds and Machines

, Volume 16, Issue 3, pp 289–302 | Cite as

The power of intervention

  • Kevin B. Korb
  • Erik Nyberg
Article

Abstract

We further develop the mathematical theory of causal interventions, extending earlier results of Korb, Twardy, Handfield, & Oppy, (2005) and Spirtes, Glymour, Scheines (2000). Some of the skepticism surrounding causal discovery has concerned the fact that using only observational data can radically underdetermine the best explanatory causal model, with the true causal model appearing inferior to a simpler, faithful model (cf. Cartwright, (2001). Our results show that experimental data, together with some plausible assumptions, can reduce the space of viable explanatory causal models to one.

Keywords

Causal models Causal discovery Faithfulness Simplicity Intervention Bayesian networks Underdetermination 

Notes

Acknowledgements

We are grateful for a Monash Research Fund grant which helped to support this work. We thank Charles Twardy, Lucas Hope, Rodney O’Donnell and anonymous referees for helpful comments on this paper.

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Copyright information

© Springer Science+Business Media 2006

Authors and Affiliations

  1. 1.School of Computer Science & Software EngineeringMonash UniversityClaytonAustralia
  2. 2.Department of History & Philosophy of ScienceUniversity of MelbourneParkvilleAustralia

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