【24h】

Evolving Heuristics for Planning

机译:不断发展的启发式规划

获取原文

摘要

In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (PRODIGY) and uses GP to acquire control rules to improve its efficiency. We also analyze two ways to introduce domain knowledge acquired by another method (HAMLET) into EVOCK: seeding the initial population and using a new operator (knowledge-based crossover). This operator combines genetic material from both an evolving population and a non-evolving population containing background knowledge. We tested these ideas in the blocksworld domain and obtained excellent results.
机译:在本文中,我们描述了evock,一种遗传编程(GP)在规划中应用的新方法。这种方法从传统的AI策划者(Prodigy)开始,并使用GP来获取控制规则以提高其效率。我们还分析了两种方式,将另一种方法(哈姆雷特)获取的域名知识引入EVOCK:播种初始群体并使用新的运算符(基于知识的交叉)。该操作员将遗传物质与含有背景知识的不断发展的人口相结合。我们在BlockSworld域中测试了这些想法,并获得了出色的结果。

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