Probability Theory and Causation: A Branching Space-Times Analysis

By Thomas Müller. British Journal for the Philosophy of Science, 2005

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We provide a formally rigorous framework for integrating singular causation, as understood by Nuel Belnap's theory of causae causantes, and objective single case probabilities. The central notion is that of a causal probability space whose sample space consists of causal alternatives. Such a probability space is generally not isomorphic to a product space. We give a causally motivated statement of the Markov condition and an analysis of the concept of screening-off. 1. Causal dependencies and probabilities 1.1Background: causation in branching space-times 1.2What are probabilities defined for?2. Basic transitions 2.1Basics of basic transitions 2.2Sets of basic transitions3. Causal probability theory 3.1Some simple cases 3.2General causal probabilities 3.3Application: probability of suprema of a chain Causal dependencies and probabilities 1.1Background: causation in branching space-times 1.2What are probabilities defined for? 1.1Background: causation in branching space-times 1.2What are probabilities defined for? Basic transitions 2.1Basics of basic transitions 2.2Sets of basic transitions 2.1Basics of basic transitions 2.2Sets of basic transitions Causal probability theory 3.1Some simple cases 3.2General causal probabilities 3.3Application: probability of suprema of a chain 3.1Some simple cases 3.2General causal probabilities 3.3Application: probability of suprema of a chain

Subfields: Atomic and Molecular Physics, and Optics, Experimental and Cognitive Psychology, History and Philosophy of Science

View Paper: https://www.semanticscholar.org/paper/e849c6b3d4c2563c88a95567cd246b84d21755a3