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Hans Reichenbach's probability logic

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In Dov M. Gabbay, John Woods & Akihiro Kanamori (eds.), Handbook of the History of Logic. Elsevier. pp. 10--357 (2004)

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  1. The Maxim of Probabilism, with special regard to Reichenbach.Miklós Rédei & Zalán Gyenis - 2021 - Synthese 199 (3-4):8857-8874.
    It is shown that by realizing the isomorphism features of the frequency and geometric interpretations of probability, Reichenbach comes very close to the idea of identifying mathematical probability theory with measure theory in his 1949 work on foundations of probability. Some general features of Reichenbach’s axiomatization of probability theory are pointed out as likely obstacles that prevented him making this conceptual move. The role of isomorphisms of Kolmogorovian probability measure spaces is specified in what we call the “Maxim of Probabilism”, (...)
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  • Reichenbach, Russell and scientific realism.Christopher Pincock - 2021 - Synthese 199 (3-4):8485-8506.
    This paper considers how to best relate the competing accounts of scientific knowledge that Russell and Reichenbach proposed in the 1930s and 1940s. At the heart of their disagreements are two different accounts of how to best combine a theory of knowledge with scientific realism. Reichenbach argued that a broadly empiricist epistemology should be based on decisions. These decisions or “posits” informed Reichenbach’s defense of induction and a corresponding conception of what knowledge required. Russell maintained that a scientific realist must (...)
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  • Dynamic and stochastic systems as a framework for metaphysics and the philosophy of science.Christian List & Marcus Pivato - 2021 - Synthese 198 (3):2551-2612.
    Scientists often think of the world as a dynamical system, a stochastic process, or a generalization of such a system. Prominent examples of systems are the system of planets orbiting the sun or any other classical mechanical system, a hydrogen atom or any other quantum–mechanical system, and the earth’s atmosphere or any other statistical mechanical system. We introduce a general and unified framework for describing such systems and show how it can be used to examine some familiar philosophical questions, including (...)
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  • On Hans Reichenbach’s inductivism.Maria Carla Galavotti - 2011 - Synthese 181 (1):95 - 111.
    One of the first to criticize the verifiability theory of meaning embraced by logical empiricists, Reichenbach ties the significance of scientific statements to their predictive character, which offers the condition for their testability. While identifying prediction as the task of scientific knowledge, Reichenbach assigns induction a pivotal role, and regards the theory of knowledge as a theory of prediction based on induction. Reichenbach's inductivism is grounded on the frequency notion of probability, of which he prompts a more flexible version than (...)
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  • On Hans Reichenbach’s inductivism.Maria Carla Galavotti - 2011 - Synthese 181 (1):95-111.
    One of the first to criticize the verifiability theory of meaning embraced by logical empiricists, Reichenbach ties the significance of scientific statements to their predictive character, which offers the condition for their testability. While identifying prediction as the task of scientific knowledge, Reichenbach assigns induction a pivotal role, and regards the theory of knowledge as a theory of prediction based on induction. Reichenbach’s inductivism is grounded on the frequency notion of probability, of which he prompts a more flexible version than (...)
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  • Can Bayesian agents always be rational? A principled analysis of consistency of an Abstract Principal Principle.Miklós Rédei & Zalán Gyenis - unknown
    The paper takes thePrincipal Principle to be a norm demanding that subjective degrees of belief of a Bayesian agent be equal to the objective probabilities once the agent has conditionalized his subjective degrees of beliefs on the values of the objective probabilities, where the objective probabilities can be not only chances but any other quantities determined objectively. Weak and strong consistency of the Abstract Principal Principle are defined in terms of classical probability measure spaces. It is proved that the Abstract (...)
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