Executive Summary
This 1989 paper details a research program using Artificial Intelligence (AI) to develop a Tactical Decision Generator (TDG) for within-visual-range fighter aircraft combat. The AI-based TDG, an evolution of the earlier FORTRAN-based Adaptive Maneuvering Logic (AML), uses a knowledge-based system to select maneuvers. Test results showed the TDG significantly outperformed both the AML program and human pilots in simulated one-on-one air combat engagements, demonstrating the benefits of AI for tactical decision-making.
Why It Matters
This document is crucial for defense analysts as it details early applications of AI in military aviation, specifically for tactical decision-making in air combat, demonstrating its potential to enhance fighter aircraft performance and pilot training.
Key Takeaways
- AI-based Tactical Decision Generators (TDG) showed significant performance improvements over traditional logic and human pilots in simulated WVR air combat.
- The AI software (TDG) proved more adaptable and easier to modify than older FORTRAN-based programs like Adaptive Maneuvering Logic (AML).
- Early AI applications focused on enhancing tactical guidance for fighter aircraft, laying groundwork for future autonomous and semi-autonomous combat systems.
Strategic Relevance
This paper highlights foundational research into AI for tactical air combat, demonstrating how early AI systems could outperform human pilots and traditional algorithms in specific scenarios. This has strategic implications for the development of autonomous combat aircraft, advanced pilot training systems, and the future of air warfare doctrine.