Automatic molecular design using evolutionary techniques
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{globus:1999:Nano,
-
title = "Automatic molecular design using evolutionary
techniques",
-
author = "Al Globus and John Lawton and Todd Wipke",
-
journal = "Nanotechnology",
-
volume = "10",
-
number = "3",
-
month = sep,
-
year = "1999",
-
pages = "290--299",
-
URL = "http://ej.iop.org/links/20/wT4K9Gv4ZjM1zl3weq3M6Q/na9312.pdf",
-
URL = "http://www.foresight.org/conference/MNT6/Papers/Globus/index.html",
-
URL = "http://alglobus.net/NASAwork/papers/Nanotechnology98/paper.html",
-
URL = "http://people.nas.nasa.gov/~globus/home.html",
-
DOI = "doi:10.1088/0957-4484/10/3/312",
-
keywords = "genetic algorithms, genetic programming",
-
abstract = "Molecular nanotechnology is the precise,
three-dimensional control of materials and devices at
the atomic scale. An important part of nanotechnology
is the design of molecules for specific purposes. This
paper describes early results using genetic software
techniques to automatically design molecules under the
control of a fitness function. The fitness function
must be capable of determining which of two arbitrary
molecules is better for a specific task. The software
begins by generating a population of random molecules.
The individual molecules in a population are then
evolved towards greater fitness by randomly combining
parts of the better existing molecules to create new
molecules. These new molecules then replace some of the
less fit molecules in the population. We apply a unique
genetic crossover operator to molecules represented by
graphs, i.e., sets of atoms and the bonds that connect
them. We present evidence suggesting that crossover
alone, operating on graphs, can evolve any possible
molecule given an appropriate fitness function and a
population containing both rings and chains. Most prior
work evolved strings or trees that were subsequently
processed to generate molecular graphs. In principle,
genetic graph software should be able to evolve other
graph-representable systems such as circuits,
transportation networks, metabolic pathways, and
computer networks.",
- }
Genetic Programming entries for
Al Globus
John Lawton
Todd Wipke
Citations