Created by W.Langdon from gp-bibliography.bib Revision:1.4771
Models and simulations, especially those working as a federation, can serve as the fitness function to determine the value or adequacy of particular solutions. In such federations, genetic programming (GP) or other EC techniques can quickly find optimal or near-optimal solutions for particular problems or situations. The user is not required to systematically search for the optimal solution; the computer accomplishes that task. The tradeoff for accepting this advantage is the requirement for the use of high performance computing resources.
In this paper we briefly describe the fundamental characteristics of EC. We also show some of the results obtained during our research and development efforts on different problems like image noise reduction and discrimination of buried unexploded ordnance. We also provide examples of how EC can be used with models and simulations to find optimum solutions to many complicated problems. This technique has great potential for use with models and simulations in a federated environment. The modelling and simulation community needs to become more aware of these powerful EC techniques so they may be applied in a wide range of fields to quickly provide solutions to the war fighter.
Distribution A. Approved for public release; distribution unlimited.",
Genetic Programming entries for Edwin Nunez Paul Agarwal Marshall McBride Ronald Liedel Claudette Owens