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Proceedings Paper

Genetic-algorithm-based optimization of a fuzzy logic resource manager for electronic attack
Author(s): James F. Smith; Robert D. Rhyne
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Paper Abstract

A fuzzy logic based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. This paper describes data mining activities related to development of the resource manager with a focus on genetic algorithm based optimization. A genetic algorithm requires the construction of a fitness function, a function that must be maximized to give optimal or near optimal results. The fitness functions are in general non- differentiable at many points and highly non-linear, neither property providing difficulty for a genetic algorithm. The fitness functions are constructed using insights from geometry, physics, engineering, and military doctrine. Examples are given as to how fitness functions are constructed including how the fitness function is averaged over a database of military scenarios. The use of a database of scenarios prevents the algorithm from having too narrow a range of behaviors, i.e., it creates a more robust solution.

Paper Details

Date Published: 6 April 2000
PDF: 12 pages
Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381764
Show Author Affiliations
James F. Smith, Naval Research Lab. (United States)
Robert D. Rhyne, Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 4057:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology II
Belur V. Dasarathy, Editor(s)

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