Applying steady state in genetic algorithm for robot behaviors
Saeed Mohammed Baneamoon, Rosalina Abdul Salam · 2008
In this paper distributed learning classifier system is used to design a control system for robot. We suggest an enhanced approach to determine the steady state values for the strength and the bid of classifiers to call genetic algorithm (GA) that works in rule discovery system in learning classifier system (LCS) in order to improve the efficiency and accuracy of robot to be able to perform its correct action.