Air combat learning from F-16 flight information

Movement sequence of a real air combat flight contains valuable information that can be used to infer artificial air combat learning. There are different ways to control unmanned aerial vehicles for a given flight path. But identifying the best move at the time being relative to an enemy air craft requires learning flight experience from real air combat fighters. This paper shows how to set up learning and control environment with adaptive neuro fuzzy inference system for maneuver decisions using real F-16 flight information. Real flight information is also utilized to justify the test results.