Genetic Programming for Multi-Timescale Modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Kumara Sastry and D. D. Johnson and 
                 David E. Goldberg and Pascal Bellon",
  title =        "Genetic Programming for Multi-Timescale Modeling",
  institution =  "Department of General Engineering University of
                 Illinois at Urbana-Champaign",
  year =         "2003",
  type =         "IlliGAL Report",
  number =       "2003014",
  address =      "117 Transportation Building, 104 S. Mathews Avenue,
                 Urbana, IL 61801, USA",
  month =        apr,
  note =         "Submitted to Physical Review Letters",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  abstract =     "A bottleneck for multi-timescale modelling is the
                 computation of activation energies (or potential energy
                 surface, PES).We explore the use of genetic programming
                 (GP)-a genetic algorithm that evolves computer
                 programs-to perform symbolic regression to create a
                 local mapping of the activation energy for any possible
                 configuration, thereby avoiding explicit calculation of
                 the entire PES. To exemplify the ideas, we apply a
                 simple GP to vacancy-assisted migration on a surface of
                 an fcc A_xB_(1-x) alloy. The GP predicts activation
                 energies within 1% error using explicit calculations
                 for less than 3% of the total active configuration.
                 These initial results scale kinetic (Monte Carlo)
                 simulations by ~9 orders in time at 300 K over
                 molecular dynamics, with less CPU time.",
  size =         "8 pages",

Genetic Programming entries for Kumara Sastry Duane D Johnson David E Goldberg Pascal Bellon