Application of genetic algorithms to autopiloting in aerial combat simulation

Dai Hyun Kim; Daniel A. Erwin; Andrew A. Kostrzewski; Jeongdal Kim; Gajendra D. Savant

doi:10.1117/12.326709

13 October 1998 Application of genetic algorithms to autopiloting in aerial combat simulation

Dai Hyun Kim, Daniel A. Erwin, Andrew A. Kostrzewski, Jeongdal Kim, Gajendra D. Savant

Proceedings Volume 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation; (1998) https://doi.org/10.1117/12.326709
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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.

Citation Download Citation

Dai Hyun Kim, Daniel A. Erwin, Andrew A. Kostrzewski, Jeongdal Kim, and Gajendra D. Savant "Application of genetic algorithms to autopiloting in aerial combat simulation", Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); https://doi.org/10.1117/12.326709

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