【24h】

Learning Regular Omega Languages

机译:学习常规欧米茄语言

获取原文

摘要

We provide an algorithm for learning an unknown regular set of infinite words, using membership and equivalence queries. Three variations of the algorithm learn three different canonical representations of omega regular languages, using the notion of families of DFAS. One is of size similar to L_$, a DFA representation recently learned using L~* [7]. The second is based on the syntactic FORC, introduced in [14]. The third is introduced herein. We show that the second can be exponentially smaller than the first, and the third is at most as large as the first two, with up to a quadratic saving with respect to the second.
机译:我们提供了一种用于学习未知常规无限单词的算法,使用会员资格和等价查询。算法的三种变体学习欧米茄常规语言的三种不同的规范表示,使用DFA的家庭的概念。一个与L_ $类似的大小,最近使用L〜* [7]学习的DFA表示。第二个是基于句法Forc,在[14]中介绍。本文介绍了第三。我们表明第二个可以是指数线的小于第一,第三个是最大的作为前两个,直到第二个节省第二。

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