English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 55184/89457 (62%)
造访人次 : 10662463      在线人数 : 23
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻

    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50530

    题名: AIN-Based Action Selection Mechanism for Soccer Robot Systems
    作者: Wang, Yin-tien;You, Zhi-jun;Chen, Chia-hsing
    贡献者: 淡江大學機械與機電工程學系
    日期: 2009
    上传时间: 2010-08-09 19:22:06 (UTC+8)
    出版者: New York: Hindawi Publishing Corporation
    摘要: Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure developed based on geometry approach will become a very complex task. In this paper, a novel action-select algorithm for soccer robots is proposed by using the concepts of artificial immune network (AIN). This AIN-based action-select provides an efficient and robust algorithm for robot role selection. Meanwhile, a reinforcement learning mechanism is applied in the proposed algorithm to enhance the response of the adaptive immune system. Simulation and experiment are carried out to verify the proposed AIN-based algorithm, and the results show that the proposed algorithm provides an efficient and applicable algorithm for mobile robots to play soccer game.
    關聯: Journal of Control Science and Engineering 2009, pp.896310(10pages)
    DOI: 10.1155/2009/896310
    显示于类别:[機械與機電工程學系暨研究所] 期刊論文


    档案 描述 大小格式浏览次数
    1687-5249_2009p896310.pdf2669KbAdobe PDF465检视/开启



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈