Discovering Novel Fighter Combat Maneuvers in Simulation: Simulating Test Pilot Creativity

This paper reports the authors' ongoing experience with a system for discovering novel fighter combat maneuvers, using a genetics-based machine learning process, and combat simulation. In effect, the genetic learning system in this application is taking the place of a test pilot, in discovering complex maneuvers from experience. The goal of this work is distinct from that of many other studies, in that innovation, and discovery of novelty, is, in itself valuable. This makes the details of aims and techniques somewhat distinct from other genetics-based machine learning research. The paper discusses the details of the application, and the motivations and details of the techniques employed. Results are presented for systems where one player adapts to a fixed strategy opponent, and where two players co-adapt. General implications of this work for other adaptive behavior applications are discussed.