A genetic programming based rule generation approach for intelligent control systems

This paper presents an intelligent control system (namely GPICS). The GPICS consists of a Symbolic Rule Controller, a Percepter and a rAdaptor. The Percepter judges whether the control system can adapt the environment. If the system is inadaptable, the rAdaptor will be activated to search the new rule to adapt the environment; otherwise, the controller will keeps on its controlling assignments. Once the rAdaptor is activated, the flexible genetic programming will be employed for searching the new rule. Simulation results of the robotic path planning showed that the GPICS method can successfully find a satisfactory path.