%0 Journal Article
%T Robot Behavior Control Based on Multi-LCS and the Artificial Potential Field<br>基于多LCS和人工势场法的机器人行为控制
%A SHAO Jie
%A YANG Jing-yu
%A <br>邵杰
%A 杨静宇
%J 计算机科学
%D 2011
%I 
%X Due to premature convergence, local optimal solution, accounting for a larger storage space and other shortcomings of genetic algorithms, a simulated control system for robot was designed by using distributed learning classifier system and Artificial potential fields to perform complex behaviors. A set of enhanced solutions of cover detectors problem was suggested and compared with each other in order to make the simulated robot more effective in choosing the appropriate behavior and improving the performance of the robot.
%K Behaviors control
%K Robot
%K Learning classifier system(LCS)
%K Covering process
%K Artificial potential fields<br>行为控制，机器人，学习分类器，覆盖算法，人工势场法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=44DDCDB836C0A98BBCB452949F9EDEB2&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=CA4FD0336C81A37A&sid=7ABC4505E3960D2B&eid=866F8A6B640835A7&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=11