Mathematics – Probability
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001aipc..568...31p&link_type=abstract
BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 20th International Workshop. AIP Conference Proceedi
Mathematics
Probability
Information Theory And Communication Theory, Probability Theory, Complex Systems, Stochastic Processes
Scientific paper
Algorithmic information content is an important fundamental idea for dealing with systems that contain or in the course of time produce large amounts of information. This notion provides a rigorous meaning to the intuitive concept of randomness, and thereby plays an important role in formal mathematics as well as in theoretical computer science. More importantly for applications, however, this idea has succeeded in providing a quantitatively precise way of characterizing the output of a deterministic dynamical system as random, or equivalently, algorithmically complex. This presentation will provide an introduction to the basic ideas of algorithmic complexity and randomness, as well to the applications of these ideas to the characterization of dynamical systems as examples of complex behavior. .
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