Active learning of timed languages is concerned with the inference of timed automata from observed timed words. The agent can query for the membership of words in the target language, or propose a candidate model and verify its equivalence to the target. The major difficulty of this framework is the inference of clock resets, central to the dynamics of timed automata, but not directly observable. Interesting first steps have already been made by restricting to the subclass of event-recording automata, where clock resets are tied to observations. In order to advance towards learning of general timed automata, we generalize this method to a new class, called reset-free event-recording automata, where some transitions may reset no clocks. This offers the same challenges as generic timed automata while keeping the simpler framework of event-recording automata for the sake of readability. Central to our contribution is the notion of invalidity, and the algorithm and data structures to deal with it, allowing on-the-fly detection and pruning of reset hypotheses that contradict observations, a key to any efficient active-learning procedure for generic timed automata.

中文翻译：

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具有不可观察重置的定时自动机的主动学习

定时语言的主动学习涉及从观察到的定时词推断定时自动机。代理可以查询目标语言中单词的成员资格，或提出候选模型并验证其与目标的等价性。这个框架的主要困难是时钟重置的推断，这是定时自动机动力学的核心，但不能直接观察。通过限制事件记录自动机的子类，已经采取了有趣的第一步，其中时钟重置与观察相关联。为了推进一般定时自动机的学习，我们将此方法推广到一个新类，称为无重置事件记录自动机，其中某些转换可能不会重置时钟。这提供了与通用定时自动机相同的挑战，同时为了可读性保留了更简单的事件记录自动机框架。我们贡献的核心是无效的概念，以及处理它的算法和数据结构，允许即时检测和修剪与观察相矛盾的重置假设，这是通用定时自动机的任何有效主动学习程序的关键.