Learning symbolic rules with a reactive with tags classifier system in robot navigation

Proceeding of: International Work-Conference on Artificial and Natural Neural Networks, IWANN'99 Alicante, Spain, June 2–4, 1999Classifier System are special production systems where conditions and actions are codified in order to learn new rules by means of Genetic Algorithms (GA). These systems combine the execution capabilities of symbolic systems and the learning capabilities of Genetic Algorithms. The Reactive with Tags Classifier System (RTCS) is able to learn symbolic rules that allow to generate sequence of actions, chaining rules among different time instants, and react to new environmental situations, considering the last environmental situation to take a decision. The capacity of RTCS to learn good rules has been prove in robotics navigation problem. Results show the suitablity of this aproximation to the navigation problem and the coherence of extracted rules