Causal explanation under indeterminism: A sampling approach

Christopher A. Merck, Samantha Kleinberg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the key uses of causes is to explain why things happen. Explanations of specific events, like an individual's heart attack on Monday afternoon or a particular car accident, help assign responsibility and inform our future decisions. Computational methods for causal inference make use of the vast amounts of data collected by individuals to better understand their behavior and improve their health. However, most methods for explanation of specific events have provided theoretical approaches with limited applicability. In contrast we make two main contributions: An algorithm for explanation that calculates the strength of token causes, and an evaluation based on simulated data that enables objective comparison against prior methods and ground truth. We show that the approach finds the correct relationships in classic test cases (causal chains, common cause, and backup causation) and in a realistic scenario (explaining hyperglycemic episodes in a simulation of type 1 diabetes).

LanguageEnglish (US)
Title of host publication30th AAAI Conference on Artificial Intelligence, AAAI 2016
PublisherAAAI press
Pages1037-1043
Number of pages7
ISBN (Electronic)9781577357605
StatePublished - Jan 1 2016
Event30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States
Duration: Feb 12 2016Feb 17 2016

Other

Other30th AAAI Conference on Artificial Intelligence, AAAI 2016
CountryUnited States
CityPhoenix
Period2/12/162/17/16

Fingerprint

Medical problems
Computational methods
Accidents
Railroad cars
Health
Sampling

Cite this

Merck, C. A., & Kleinberg, S. (2016). Causal explanation under indeterminism: A sampling approach. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016 (pp. 1037-1043). AAAI press.
Merck, Christopher A. ; Kleinberg, Samantha. / Causal explanation under indeterminism : A sampling approach. 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, 2016. pp. 1037-1043
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Merck, CA & Kleinberg, S 2016, Causal explanation under indeterminism: A sampling approach. in 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, pp. 1037-1043, 30th AAAI Conference on Artificial Intelligence, AAAI 2016, Phoenix, United States, 2/12/16.

Causal explanation under indeterminism : A sampling approach. / Merck, Christopher A.; Kleinberg, Samantha.

30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, 2016. p. 1037-1043.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Merck CA, Kleinberg S. Causal explanation under indeterminism: A sampling approach. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press. 2016. p. 1037-1043