Abstract: Intelligent ‘live vs. virtual’ counterwork is an important function requirement for modern advanced fighter’s embedded training system. Autonomous decision making and control technology plays a vital role in the development of future air battle equipment. The combination of the current requirement and developing technology creates the concept of air combat intelligent virtual training partner. Advanced decision-making and control technology enables the intelligent virtual training partner to help pilots fulfill complex tactics training, during which live scenarios and amount of data provide ideal validation environment and continuous optimization opportunities. As an air combat tactics expert that allows self-learning and self-evolving, the intelligent training partner is able to get consistent optimization in counterwork with pilots and itself. And it can be applied into future unmanned air battle systems when it has tactical advantages equal even superior to pilots. The four basic capability requirements for intelligent virtual training partner are presented: intelligent decision making, knowledge learning, self-countering and optimizing, and parameterization representing. The key technologies involved in these requirements are analyzed. A prototype solution is built based on fuzzy inference, neural network and reinforcement learning, and their basic capabilities and current air combat level were shown in this paper. In the future, more models and algorithms can be validated and optimized in the framework of intelligent virtual training partner.

Key words: embedded training system, intelligent virtual training partner, autonomous air combat, fuzzy inference, neural network, reinforcement learning