Red Teaming with Coevolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Hingston:2011:RTwC,
-
author = "Philip Hingston and Mike Preuss",
-
title = "Red Teaming with Coevolution",
-
pages = "1155--1163",
-
booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
-
year = "2011",
-
editor = "Alice E. Smith",
-
month = "5-8 " # jun,
-
address = "New Orleans, USA",
-
organization = "IEEE Computational Intelligence Society",
-
publisher = "IEEE Press",
-
keywords = "genetic algorithms, genetic programming, red teaming,
coevolution, Coevolutionary systems, Evolutionary
simulation-based optimization, Real-world
applications",
-
ISBN = "0-7803-8515-2",
-
DOI = "doi:10.1109/CEC.2011.5949747",
-
size = "9 pages",
-
abstract = "we present a coevolutionary algorithm designed to be
used as a computational tool to assist in red teaming
studies. In these applications, analysts seek to
understand the strategic and tactical options available
to each side in a conflict situation. Combining
scenario simulations with a coevolutionary search of
parameter space is an approach that has many
attractions. We argue that red teaming applications are
sufficiently different from many others where
coevolution is used so that specially designed
algorithms can bring advantages. We illustrate by
presenting a new algorithm that simultaneously evolves
strong strategies along with dangerous
counter-strategies. We test the new algorithm on two
example problems: an abstract problem with some
difficult characteristics; and a practical red teaming
scenario. Experiments show that the new algorithm is
able to solve the abstract problem well, and that it is
able to provide useful insights on the red teaming
scenario.",
-
notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Philip Hingston
Mike Preuss
Citations