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Temporally Asymmetric Inference in a Markov Process

Published online by Cambridge University Press:  01 April 2022

Elliott Sober
Elliott Sober*
Affiliation:
Department of Philosophy University of Wisconsin
*
‡Send reprint requests to the author, Department of Philosophy, University of Wisconsin-Madison, 5185 Helen C. White Hall, 600 North Park Street, Madison, WI 53706.
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Abstract

A model of a Markov process is presented in which observing the present state of a system is asymmetrically related to inferring the system's future and inferring its past. A likelihood inference about the system's past state, based on observing its present state, is justified no matter what the parameter values in the model happen to be. In contrast, a probability inference of the system's future state, based on observing its present state, requires further information about the parameter values.

Information

Type
Research Article
Information
Philosophy of Science , Volume 58 , Issue 3 , September 1991 , pp. 398 - 410
Copyright
Copyright © 1991 The Philosophy of Science Association

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Footnotes

†

I am grateful to Martin Barrett, Ellery Eells, Malcolm Forster, and an anonymous referee for valuable comments.

References

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