Abstract

Training in flight simulators will be more effective if the agents involved in the simulation behave realistically. Accomplishing this requires that the automated agents be under autonomous, intelligent control. We are using the Soar cognitive architecture to implement intelligent agents that behave as much like humans as possible. In order to approximate human behavior, the agents must integrate planning and reaction in real time, adapt to new and unexpected situations, learn with experience, and exhibit the cognitive limitations and strengths of humans. This paper describes two simple tactical flight scenarios and the knowledge required for an agent to complete them. In addition, the paper describes an implemented agent model that performs in limited tactical scenarios on three different flight simulators. The goal of this research is to construct intelligent, automated agents for flight simulators that are used to train navy pilots in flight tactics. When pilots train in tactical ...

Citations