Philosophy Compass 13 (1):e12470 (2018)

Authors
David Danks
Carnegie Mellon University
Daniel Malinsky
Carnegie Mellon University
Abstract
Many investigations into the world, including philosophical ones, aim to discover causal knowledge, and many experimental methods have been developed to assist in causal discovery. More recently, algorithms have emerged that can also learn causal structure from purely or mostly observational data, as well as experimental data. These methods have started to be applied in various philosophical contexts, such as debates about our concepts of free will and determinism. This paper provides a “user's guide” to these methods, though not in the sense of specifying exact button presses in a software package. Instead, we explain the larger “pipeline” within which these methods are used and discuss key steps in moving from initial research idea to validated causal structure.
Keywords No keywords specified (fix it)
Categories (categorize this paper)
Reprint years 2018
DOI 10.1111/phc3.12470
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

PhilArchive copy


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 55,981
Through your library

References found in this work BETA

Making Things Happen. A Theory of Causal Explanation.Michael Strevens - 2007 - Philosophy and Phenomenological Research 74 (1):233-249.
Causation, Prediction, and Search.Peter Spirtes, Clark Glymour & Richard Scheines - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
The Direction of Time.Henryk Mehlberg - 1962 - Philosophical Review 71 (1):99.
The Problem of Variable Choice.James Woodward - 2016 - Synthese 193 (4):1047-1072.

View all 12 references / Add more references

Citations of this work BETA

Add more citations

Similar books and articles

Expertise and Mixture in Automatic Causal Discovery.Joseph Daniel Ramsey - 2001 - Dissertation, University of California, San Diego
Causal Conclusions That Flip Repeatedly and Their Justification.Kevin T. Kelly & Conor Mayo-Wilson - 2010 - Proceedings of the Twenty Sixth Conference on Uncertainty in Artificial Intelligence 26:277-286.
The Power of Intervention.Kevin B. Korb & Erik Nyberg - 2006 - Minds and Machines 16 (3):289-302.
The Limits of Piecemeal Causal Inference.Conor Mayo-Wilson - 2014 - British Journal for the Philosophy of Science 65 (2):213-249.
Discovering Quantum Causal Models.Sally Shrapnel - 2019 - British Journal for the Philosophy of Science 70 (1):1-25.
Quantum Causal Modelling.Fabio Costa & Sally Shrapnel - 2016 - New Journal of Physics 18 (6):063032.
The Three Faces of Faithfulness.Jiji Zhang & Peter Spirtes - 2016 - Synthese 193 (4):1011-1027.
Amalgamating Evidence of Dynamics.David Danks & Sergey Plis - 2019 - Synthese 196 (8):3213-3230.

Analytics

Added to PP index
2017-11-23

Total views
63 ( #156,647 of 2,403,496 )

Recent downloads (6 months)
4 ( #197,513 of 2,403,496 )

How can I increase my downloads?

Downloads

My notes