Algorithmic Information Theory
by Peter D. Gruenwald, Paul M.B. Vitanyi
Publisher: CWI 2007
Number of pages: 37
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain the main concepts of this quantitative approach to defining 'information'. We discuss the extent to which Kolmogorov's and Shannon's information theory have a common purpose, and where they are fundamentally different.
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by Felix Effenberger - arXiv
This chapter is supposed to give a short introduction to the fundamentals of information theory, especially suited for people having a less firm background in mathematics and probability theory. The focus will be on neuroscientific topics.
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The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical.
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