Subjectivity, Bayesianism, and Causality
Bayesian probability theory is one of the most successful frameworks to model reasoning under uncertainty. Its defining property is the interpretation of probabilities as degrees of belief in propositions about the state of the world relative to an inquiring subject. This essay examines the notion o...
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Main Author | |
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Format | Journal Article |
Language | English |
Published |
15.07.2014
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Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.1407.4139 |
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Summary: | Bayesian probability theory is one of the most successful frameworks to model
reasoning under uncertainty. Its defining property is the interpretation of
probabilities as degrees of belief in propositions about the state of the world
relative to an inquiring subject. This essay examines the notion of
subjectivity by drawing parallels between Lacanian theory and Bayesian
probability theory, and concludes that the latter must be enriched with causal
interventions to model agency. The central contribution of this work is an
abstract model of the subject that accommodates causal interventions in a
measure-theoretic formalisation. This formalisation is obtained through a
game-theoretic Ansatz based on modelling the inside and outside of the subject
as an extensive-form game with imperfect information between two players.
Finally, I illustrate the expressiveness of this model with an example of
causal induction. |
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DOI: | 10.48550/arxiv.1407.4139 |