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Towards General Algorithms for Grammatical Inference

机译:走向语法推断的通用算法

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Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of strings, and a set of features or tests that constrain various inference rules. Using this general framework, which we cast as a process of logical inference, we re-analyse Angluin's famous lstar algorithm and several recent algorithms for the inference of context-free grammars and multiple context-free grammars. Finally, to illustrate the advantages of this approach, we extend it to the inference of functional transductions from positive data only, and we present a new algorithm for the inference of finite state transducers.
机译:可以将许多用于语法推断的算法视为更通用算法的实例,该算法维护一组原始元素(在分布上定义字符串集)以及一组约束各种推理规则的特征或测试。使用我们作为逻辑推理过程进行转换的通用框架,我们重新分析了Angluin著名的lstar算法以及几种用于上下文无关文法和多种上下文无关文法的最新算法。最后,为了说明该方法的优点,我们将其扩展到仅从正数据推断功能转换,然后提出了一种用于推断有限状态传感器的新算法。

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