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Proceedings Paper

Application of genetic algorithms to autopiloting in aerial combat simulation
Author(s): Dai Hyun Kim; Daniel A. Erwin; Andrew A. Kostrzewski; Jeongdal Kim; Gajendra D. Savant
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Paper Abstract

An autopilot algorithm that controls a fighter aircraft in simulated aerial combat is presented. A fitness function, whose arguments are the control settings of the simulated fighter, is continuously maximized by a fuzzied genetic algorithm. Results are presented for one-to-one combat simulated on a personal computer. Generalization to many-to-many combat is discussed.

Paper Details

Date Published: 13 October 1998
PDF: 6 pages
Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326709
Show Author Affiliations
Dai Hyun Kim, Physical Optics Corp. (United States)
Daniel A. Erwin, Univ. of Southern California (United States)
Andrew A. Kostrzewski, Physical Optics Corp. (United States)
Jeongdal Kim, Los Angeles Metropolitan Water District (United States)
Gajendra D. Savant, Physical Optics Corp. (United States)


Published in SPIE Proceedings Vol. 3455:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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