Evolving Programs and Solutions Using Genetic Programming with Application to Learning and Adaptive Control
This paper discusses two feasibility studies of Genetic Programming (GP) to the field of control theory, GP being a method inspired from nature where the goal is to create a computer program automatically from high-level statements of problems' requirements. The first feasibility study derives from stability theory and deals with evolving a program that can solve discrete-time Lyapunov equations.
