Title :
Intelligent Exploration Method to Adapt Exploration Rate in XCS, Based on Adaptive Fuzzy Genetic Algorithm
Author :
Hamzeh, Ali ; Rahmani, Adel ; Parsa, Nahid
Author_Institution :
Dept. of Comput. Eng., Iran Univ. of Sci. & Technol., Tehran
Abstract :
In this paper, we propose an extension to the intelligent exploration method which is introduced in our previous work. IEM is an intelligent exploration method that is used to tune the exploration rate in XCS. In this paper we improve the IEM´s performance using a learning fuzzy controller instead of the static one in IEM. The new system is called IEMII (IEM 2) and is compared with the IEM and the traditional XCS in some benchmark problems
Keywords :
adaptive systems; genetic algorithms; learning (artificial intelligence); adaptive fuzzy genetic algorithm; exploration-exploitation dilemma; intelligent exploration method; learning classifier systems; learning fuzzy controller; Adaptive algorithm; Adaptive systems; Costs; Fuzzy control; Genetic algorithms; Genetic engineering; Guidelines; Machine learning; Paper technology; Performance gain; Exploration/Exploitation Dilemma; Learning Classifier Systems; XCS;
Conference_Titel :
Cybernetics and Intelligent Systems, 2006 IEEE Conference on
Conference_Location :
Bangkok
Print_ISBN :
1-4244-0023-6
DOI :
10.1109/ICCIS.2006.252271
