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Pattern Discovery and Computational Mechanics

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Author Info
Cosma Rohilla Shalizi
James P. Crutchfield
Abstract

Computational mechanics is a method for discovering, describing and quantifying patterns, using tools from statistical physics. It contructs optimal, minimal models of stochastic processes and their underlying causal structures. These models tell us about the intrinsic computation embedded within a process -- how it stores and transforms information. Here we summarize the mathematics of computational mechanics, especially recent optimality and uniqueness results. We also expound the principles and motivations underlying computational mechanics, emphasizing its connections to the minimum description length principle, PAC theory, and other aspects of machine learning.

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Publisher Info
Paper provided by Santa Fe Institute in its series Working Papers with number 00-01-008.

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Date of creation: Jan 2000
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Handle: RePEc:wop:safiwp:00-01-008

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Related research
Keywords: Pattern discovery; machine learning; computational mechanics; information; induction; e-machine.;

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This page was last updated on 2009-12-16.


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