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Philosophical Applications of Kolmogorov's Complexity Measure

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  • Itzhak Gilboa

Abstract

Kolmogorov has defined the complexity of a sequence of bits to be the minimal size of (the description of) a Turing machine which can regenerate the given sequence. This paper contains two notes on possible applications of this complexity notion to philosophy in general and the philosophy of science in particular. The first presents simplicism--a theory prescribing that people would tend to choose the simplest theory to explain observations, where "simple" is defined by (a version of) Kolmogorov's measure. The second suggests a reinterpretation of a simple observation, saying that reality is almost surely too complex to understand, terms such as "good" and "evil" almost surely too complex to define, and so forth.

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Paper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number 923.

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Date of creation: Oct 1990
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Handle: RePEc:nwu:cmsems:923

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Cited by:
  1. Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003. "Fact-Free Learning," PIER Working Paper Archive 03-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  2. Kumabe, Masahiro & Mihara, H. Reiju, 2008. "Computability of simple games: A characterization and application to the core," Journal of Mathematical Economics, Elsevier, vol. 44(3-4), pages 348-366, February.
  3. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Knowledge and Planning," Discussion Papers 1127, Northwestern University, Center for Mathematical Studies in Economics and Management Science.

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