Incremental Learning of Definite Clause Grammars and Application to Machine Learning

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This research project aims to establish efficient incremental learning of a wider class of formal grammars and its applications to machine learning, based on the previous works on learning context-free grammars(CFGs) and definite clause grammars(DCGs). The results includes analysis and improvement of search strategy for rule sets, learning one-way cellular automata(OCAs) recognizing formal languages, learning grammars by using Boolean satisfiability problem(SAT) solver and learning linear-indexed grammars(LIGs).