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A note on the complexity of the causal ordering problem

Gonçalves, Bernardo and Porto, Fabio (2016) A note on the complexity of the causal ordering problem. Artificial Intelligence, 238. pp. 154-165. ISSN 00043702

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Abstract

In this note we provide a concise report on the complexity of the causal ordering problem, originally introduced by Simon to reason about causal dependencies implicit in systems of mathematical equations. We show that Simon’s classical algorithm to infer causal ordering is NP-Hard—an intractability previously guessed but never proven. We present then a detailed account based on Nayak’s suggested algorithmic solution (the best available), which is dominated by computing transitive closure—bounded in time by O(|V|·|S|), where S(E, V) is the input system structure composed of a set E of equations over a set V of variables with number of variable appearances (density) |S|. We also comment on the potential of causal ordering for emerging applications in large-scale hypothesis management and analytics.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Gonçalves, Bernardo
Porto, Fabio
Subjects: Specific Sciences > Artificial Intelligence > Classical AI
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Cognitive Science > Concepts and Representations
Depositing User: Dr. Bernardo Gonçalves
Date Deposited: 12 Apr 2021 02:30
Last Modified: 12 Apr 2021 02:30
Item ID: 18540
Journal or Publication Title: Artificial Intelligence
Official URL: http://doi.org/10.1016/j.artint.2016.06.004
DOI or Unique Handle: 10.1016/j.artint.2016.06.004
Subjects: Specific Sciences > Artificial Intelligence > Classical AI
Specific Sciences > Cognitive Science > Computation
Specific Sciences > Cognitive Science > Concepts and Representations
Date: 2016
Page Range: pp. 154-165
Volume: 238
ISSN: 00043702
URI: https://philsci-archive.pitt.edu/id/eprint/18540

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