• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Improvements to Autonomous Forces Through the Use of Genetic Algorithms and Rule Base Enhancement.
【24h】

Improvements to Autonomous Forces Through the Use of Genetic Algorithms and Rule Base Enhancement.

机译：通过使用遗传算法和规则库增强来改进自治力量。

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This thesis discusses two approaches to enhancing the performance of intelligent autonomous agents in a computer combat simulation environment so that their performances more closely model the tactical decisions made by human players. The first approach addresses incorporating a genetic algorithm (GA) into the NPSNET Autonomous Force Expert System (NPSNET AF), while the second approach focuses on enriching the existing rule base and decision strategies. First, we develop a functional genetic algorithm with the intent of providing dynamic, real-time learning within the NPSNET AF. However, we conclude that the GA is better suited for a static problem, such as artillery battery registering of fires, rather than for the dynamic battlefield of the NPSNET. Second, we enrich the NPSNET AF expert system by enabling it to choose from among four formations and by providing a mechanism for transitioning between them. We enable the expert system to make formation decisions based upon general terrain characteristics and target location. Genetic algorithm, Autonomous forces, NPSNET, Expert system, Rule base enhancement.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号