# Subjectivity, Bayesianism, and causality

@article{Ortega2015SubjectivityBA, title={Subjectivity, Bayesianism, and causality}, author={Pedro A. Ortega}, journal={ArXiv}, year={2015}, volume={abs/1407.4139} }

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…

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## 2 Citations

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## References

SHOWING 1-10 OF 97 REFERENCES

Causation, prediction, and search

- Mathematics
- 1993

What assumptions and methods allow us to turn observations into causal knowledge, and how can even incomplete causal knowledge be used in planning and prediction to influence and control our…

The Algebra of Probable Inference

- Computer Science, Mathematics
- 1962

In Algebra of Probable Inference, Richard T. Cox develops and demonstrates that probability theory is the only theory of inductive inference that abides by logical consistency, thereby establishing, for the first time, the legitimacy of probability theory as formalized by Laplace in the 18th century.

Bayesian Causal Induction

- Computer Science, MathematicsNIPS 2011
- 2011

A Bayesian model of causal induction is outlined where beliefs over competing causal hypotheses are modeled using probability trees and it is illustrated why, in the general case, the authors need interventions plus constraints on their causal hypotheses in order to extract causal information from their experience.

Theory of Games and Economic Behavior

- EconomicsNature
- 1946

THIS book is based on the theory that the economic man attempts to maximize his share of the world's goods and services in the same way that a participant in a game involving many players attempts to…

How the Laws of Physics Lie.

- Philosophy
- 1990

Nancy Cartwright argues for a novel conception of the role of fundamental scientific laws in modern natural science. If we attend closely to the manner in which theoretical laws figure in the…

The art of causal conjecture

- Computer Science
- 1996

The Art of Causal Conjecture shows that causal ideas can be equally important in theory and by bringing causal ideas into the foundations of probability allows causal conjectures to be more clearly quantified, debated, and confronted by statistical evidence.

Causality: Models, Reasoning and Inference

- Philosophy
- 2000

1. Introduction to probabilities, graphs, and causal models 2. A theory of inferred causation 3. Causal diagrams and the identification of causal effects 4. Actions, plans, and direct effects 5.…

Probability theory: the logic of science

- 2005

This is a remarkable book by a remarkable scientist. E. T. Jaynes was a physicist, principally theoretical, who found himself driven to spend much of his life advocating, defending and developing a…

FUNDAMENTALS OF STATISTICAL CAUSALITY

- Psychology
- 2007

2 Preface Traditionally, Statistics has been concerned with uncovering and describing associations, and statisticians have been wary of causal interpretations of their findings. But users of…

Probabilistic Theories of Causation

- Psychology
- 1988

Probabilistic theories of causation have received relatively little attention. This is understandable, perhaps, since presentations are usually rather technical. But the neglect is unfortunate. The…