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Carnapian inductive logic for Markov chains

Erkenntnis 35 (1-3):439 - 460 (1991)

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  1. Cleansing the Doors of Perception: Aristotle on Induction.John R. Welch - 2001 - In Konstantine Boudouris (ed.), Greek Philosophy and Epistemology. International Association for Greek Philosophy.
    This chapter has two objectives. The first is to clarify Aristotle’s view of the first principles of the sciences. The second is to stake out a critical position with respect to this view. The paper sketches an alternative to Aristotle’s intuitionism based in part on the use of quantitative inductive logics.
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  • Universal Prediction.Tom F. Sterkenburg - 2018 - Dissertation, University of Groningen
    In this thesis I investigate the theoretical possibility of a universal method of prediction. A prediction method is universal if it is always able to learn from data: if it is always able to extrapolate given data about past observations to maximally successful predictions about future observations. The context of this investigation is the broader philosophical question into the possibility of a formal specification of inductive or scientific reasoning, a question that also relates to modern-day speculation about a fully automatized (...)
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  • Statistics as Inductive Inference.Jan-Willem Romeijn - unknown
    An inductive logic is a system of inference that describes the relation between propositions on data, and propositions that extend beyond the data, such as predictions over future data, and general conclusions on all possible data. Statistics, on the other hand, is a mathematical discipline that describes procedures for deriving results about a population from sample data. These results include predictions on future samples, decisions on rejecting or accepting a hypothesis about the population, the determination of probability assignments over such (...)
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  • Objectivity and Bias.Gordon Belot - 2017 - Mind 126 (503):655-695.
    The twin goals of this essay are: to investigate a family of cases in which the goal of guaranteed convergence to the truth is beyond our reach; and to argue that each of three strands prominent in contemporary epistemological thought has undesirable consequences when confronted with the existence of such problems. Approaches that follow Reichenbach in taking guaranteed convergence to the truth to be the characteristic virtue of good methods face a vicious closure problem. Approaches on which there is a (...)
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  • Putnam’s Diagonal Argument and the Impossibility of a Universal Learning Machine.Tom F. Sterkenburg - 2019 - Erkenntnis 84 (3):633-656.
    Putnam construed the aim of Carnap’s program of inductive logic as the specification of a “universal learning machine,” and presented a diagonal proof against the very possibility of such a thing. Yet the ideas of Solomonoff and Levin lead to a mathematical foundation of precisely those aspects of Carnap’s program that Putnam took issue with, and in particular, resurrect the notion of a universal mechanical rule for induction. In this paper, I take up the question whether the Solomonoff–Levin proposal is (...)
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  • Bayesian Orgulity.Gordon Belot - 2013 - Philosophy of Science 80 (4):483-503.
    A piece of folklore enjoys some currency among philosophical Bayesians, according to which Bayesian agents that, intuitively speaking, spread their credence over the entire space of available hypotheses are certain to converge to the truth. The goals of the present discussion are to show that kernel of truth in this folklore is in some ways fairly small and to argue that Bayesian convergence-to-the-truth results are a liability for Bayesianism as an account of rationality, since they render a certain sort of (...)
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  • Putnam's Diagonal Argument and the Impossibility of a Universal Learning Machine.Tom F. Sterkenburg - unknown
    The diagonalization argument of Putnam denies the possibility of a universal learning machine. Yet the proposal of Solomonoff and Levin promises precisely such a thing. In this paper I discuss how their proposed measure function manages to evade Putnam's diagonalization in one respect, only to fatally fall prey to it in another.
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  • Carnapian Inductive Logic for a Value Continuum.Brian Skyrms - 1993 - Midwest Studies in Philosophy 18 (1):78-89.
  • Probability and Logic.Kenny Easwaran - 2014 - Philosophy Compass 9 (12):876-883.
    Probability and logic are two branches of mathematics that have important philosophical applications. This article discusses several areas of intersection between them. Several involve the role for probability in giving semantics for logic or the role of logic in governing assignments of probability. Some involve probability over non-classical logic or self-referential sentences.
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  • Emergence of Information Transfer by Inductive Learning.Simon M. Huttegger & Brian Skyrms - 2008 - Studia Logica 89 (2):237-256.
    We study a simple game theoretic model of information transfer which we consider to be a baseline model for capturing strategic aspects of epistemological questions. In particular, we focus on the question whether simple learning rules lead to an efficient transfer of information. We find that reinforcement learning, which is based exclusively on payoff experiences, is inadequate to generate efficient networks of information transfer. Fictitious play, the game theoretic counterpart to Carnapian inductive logic and a more sophisticated kind of learning, (...)
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  • Vagueness and Inductive Molding.J. R. Welch - 2007 - Synthese 154 (1):147-172.
    Vagueness is epistemic, according to some. Vagueness is ontological, according to others. This article deploys what I take to be a compromise position. Predicates are coined in specific contexts for specific purposes, but these limited practices do not automatically fix the extensions of predicates over the domain of all objects. The linguistic community using the predicate has rarely considered, much less decided, all questions that might arise about the predicate’s extension. To this extent, the ontological view is correct. But a (...)
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