Distilling Free-Form Natural Laws from Experimental Data

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Science09:Schmidt,
  author =       "Michael Schmidt and Hod Lipson",
  title =        "Distilling Free-Form Natural Laws from Experimental
                 Data",
  journal =      "Science",
  year =         "2009",
  volume =       "324",
  number =       "5923",
  pages =        "81--85",
  month =        "3 " # apr,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://ccsl.mae.cornell.edu/sites/default/files/Science09_Schmidt.pdf",
  DOI =          "doi:10.1126/science.1165893",
  size =         "4.5 pages",
  abstract =     "For centuries, scientists have attempted to identify
                 and document analytical laws that underlie physical
                 phenomena in nature. Despite the prevalence of
                 computing power, the process of finding natural laws
                 and their corresponding equations has resisted
                 automation. A key challenge to finding analytic
                 relations automatically is defining algorithmically
                 what makes a correlation in observed data important and
                 insightful. We propose a principle for the
                 identification of nontriviality. We demonstrated this
                 approach by automatically searching motion-tracking
                 data captured from various physical systems, ranging
                 from simple harmonic oscillators to chaotic
                 double-pendula. Without any prior knowledge about
                 physics, kinematics, or geometry, the algorithm
                 discovered Hamiltonians, Lagrangians, and other laws of
                 geometric and momentum conservation. The discovery rate
                 accelerated as laws found for simpler systems were used
                 to bootstrap explanations for more complex systems,
                 gradually uncovering the alphabet used to describe
                 those systems.",
  notes =        "Eureqa Pareto parsimony v. accuracy www.sciencemag.org
                 http://www.sciencemag.org/cgi/data/324/5923/81/DC1/1
                 http://www.sciencemag.org/content/vol324/issue5923/images/data/81/DC1/1165893s1.mpg
                 3mins 43seconds
                 http://www.sciencemag.org/content/vol324/issue5923/images/data/81/DC1/invar_datasets.zip

                 Entered 2010 HUMIES GECCO 2010
                 http://www.genetic-programming.org/combined.php

                 \cite{Waltz:2009:science}",
}

Genetic Programming entries for Michael D Schmidt Hod Lipson

Citations