English(EN) SMT-Based Active Learning of Weighted Automata

新的基于SMT的算法可高效学习加权自动机

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-08 14:01

研究人员开发了一种新的基于SMT的非确定性加权自动机（WFA）主动学习算法。该方法为现有技术提供了一种实用且稳健的替代方案，可生成最小化的WFA，并在实验评估中表现出强大的性能。该算法是参数化的，如果终止则保证生成最小化的WFA，并对有限半环证明了终止条件。 AI

影响引入了一种学习加权自动机的新算法，有望提高形式语言处理任务中学习模型的效率和规模。

排序理由该集群包含一篇详细介绍新算法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Alexandra Silva · 2026-05-08 14:01

SMT驱动的加权自动机主动学习

We present an SMT-based active learning algorithm for nondeterministic weighted automata (WFAs) as a practical and robust alternative to Hankel/L*-style methods. Our algorithm is parametric in a given semiring and, if it terminates, guaranteed to produce minimal WFAs. We prove pa…