IDS：一种有限自动机的增量式学习算法
IDS: An Incremental Learning Algorithm for Finite Automata
摘要：
提出了一种新的增量学习算法IDS。该算法基于Angluin81中引入的区分序列的概念。我们给出了一个严格的证明，这两个版本的学习算法正确学习的限制。最后，我们提出了一个实证性能分析，比较这两种算法，侧重于学习时间和不同类型的学习查询。我们的结论是，IDS是一个有效的算法自动机学习的软件工程应用，如测试和模型推理。
英文摘要：
We present a new algorithm IDS for incremental learning of deterministic finite automata (DFA). This algorithm is based on the concept of distinguishing sequences introduced in (Angluin81). We give a rigorous proof that two versions of this learning algorithm correctly learn in the limit. Finally we present an empirical performance analysis that compares these two algorithms, focussing on learning times and different types of learning queries. We conclude that IDS is an efficient algorithm for software engineering applications of automata learning, such as testing and model inference.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
