EVOLVING PROTOTYPE CONTROL RULES FOR A DYNAMIC SYSTEM

作     者：FOGARTY, TC HUANG, R 

作者机构：University of the West of England Bristol BS16 1QY UK 

出 版 物：《KNOWLEDGE-BASED SYSTEMS》 (知识库系统)

年 卷 期：1994年第7卷第2期

页      面：142-145页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：British Council 

主　　题：GENETIC ALGORITHMS PROTOTYPE CONTROL RULES NEAREST-NEIGHBOR ALGORITHMS 

摘      要：The genetic algorithm is used for the learning of prototype control rules for a dynamic system. Prototype control rules are point based, but only a limited number of points in the state space with associated control actions are learned. The nearest-neighbour algorithm is used to decide which of the rules to fire in any situation. The example of a simulated cart-pole balancing problem is used to demonstrate the advantages of this approach over other rule-learning methods.