Riccardo Stabile
Broschiertes Buch

Learning Subsequential Transducers. A Categorical Approach

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Master's Thesis from the year 2024 in the subject Computer Sciences - Artificial Intelligence, Università degli Studi di Milano (Dipartimento di Matematica), course: Corso di Laurea Magistrale in Matematica, language: English, abstract: In this thesis, an algorithm for learning subsequential transducers is presented from two different perspectives: as an extension of Angluin's algorithm for learning deterministic finite automata and as an instantiation of a more generic categorical algorithm valid for a larger class of automata. The adopted categorical approach considers automata as functors ...