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  1. Strict process machine complexity.Ferit Toska - 2014 - Archive for Mathematical Logic 53 (5-6):525-538.
    We introduce a notion of description for infinite sequences and their sets, and a corresponding notion of complexity. We show that for strict process machines, complexity of a sequence or of a subset of Cantor space is equal to its effective Hausdorff dimension.
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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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  • Randomness? What Randomness?Klaas Landsman - 2020 - Foundations of Physics 50 (2):61-104.
    This is a review of the issue of randomness in quantum mechanics, with special emphasis on its ambiguity; for example, randomness has different antipodal relationships to determinism, computability, and compressibility. Following a philosophical discussion of randomness in general, I argue that deterministic interpretations of quantum mechanics are strictly speaking incompatible with the Born rule. I also stress the role of outliers, i.e. measurement outcomes that are not 1-random. Although these occur with low probability, their very existence implies that the no-signaling (...)
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  • Randomness, computation and mathematics.Rod Downey - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 162--181.