Genetic Programming for Multi-Timescale Modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@TechReport{sastry:2003014,

• 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 = "ftp://ftp-illigal.ge.uiuc.edu/pub/papers/IlliGALs/2003014.ps.Z",
• URL = "http://arXiv.org/abs/cond-mat/0405415",
• 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

Citations