2007/03/12 by PierGianLuca Porta Mana, P. G. L. Porta Mana, Mana, P. G. L. Porta +6 · 2 citations
Arts and Humanities · Computer Science · Mathematics · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Artificial intelligence #Bayesian probability #Complement (music) #Computer science #Context (archaeology) #Data Analysis #Epistemology #FOS: Computer and information sciences #FOS: Physical sciences #Interpretation (philosophy) #Laplace transform #Mathematical analysis #Mathematical and Theoretical Analysis #Mathematical economics #Mathematics #Meaning (existential) #Philosophy #Philosophy and History of Science #Pure mathematics #Quantum Physics (quant-ph) #Representation (politics) #Representation theorem #Statistical Mechanics and Entropy #Statistics and Probability (physics.data-an) #cs.AI #physics.data-an #quant-ph
paper · pdf · doi:10.48550/arxiv.physics/0703126
published in arXiv (Cornell University) (Cornell University) · 38 pages, 1 figure. V2: altered discussion on some points, corrected typos, added references
openalex publication_date 2007/03/12 · arxiv created 2007/04/29 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
An approach to induction is presented, based on the idea of analysing the context of a given problem into `circumstances'. This approach, fully Bayesian in form and meaning, provides a complement or in some cases an alternative to that based on de Finetti's representation theorem and on the notion of infinite exchangeability. In particular, it gives an alternative interpretation of those formulae that apparently involve `unknown probabilities' or `propensities'. Various advantages and applications of the presented approach are discussed, especially in comparison to that based on exchangeability. Generalisations are also discussed.