A Counter Example to Theorems of Cox and Fine
arXiv:1105.5450 · doi:10.1613/jair.536
Abstract
Cox's well-known theorem justifying the use of probability is shown not to hold in finite domains. The counterexample also suggests that Cox's assumptions are insufficient to prove the result even in infinite domains. The same counterexample is used to disprove a result of Fine on comparative conditional probability.
References in corpus (2)
Cited by in corpus (14)
- On the Brittleness of Bayesian Inference
- Foundations for conditional probability
- Cox's Theorem and the Jaynesian Interpretation of Probability
- Generalized probabilities in statistical theories
- General Robust Bayes Pseudo-Posterior: Exponential Convergence results with Applications
- The Cox Theorem: Unknowns And Plausible Value
- From Propositional Logic to Plausible Reasoning: A Uniqueness Theorem
- Born Rule and Logical Inference in Quantum Mechanics
- Deterministic modal Bayesian Logic: derive the Bayesian inference within the modal logic T
- Inference with Discriminative Posterior
- What is the plausibility of probability?(revised 2003, 2015)
- Axioms for Rational Reinforcement Learning
- Deterministic Bayesian Logic
- Cox's Theorem Revisited