Simulation-based learning in knowledge-based controllers

A methodology is presented to transform knowledge-based controllers into adaptive structure representations. These adaptive controllers are then evolved using automatic directed search methods, where the performance of the trial controllers is evaluated through simulation in a synthetic environment. This automatically acquired knowledge is incorporated back into a revised knowledge-based controller. This process is developed and demonstrated using the flight and fire controllers of a simulated airborne laser system as a testbed