learning automata; deterministic automata; learning (artificial intelligence); computational complexity; evolutionary computation; learning deterministic finite automata; machine learning; evolutionary computation; transition matrix; state labels; final states; size reduction; complexity reduction; search space; Tomita languages; random DFA; induction problems; target size; training set density; Tomita set; fitness evaluations; evolutionary methods; evidence driven state merging; learning algorithms;
机译:Python中灵活的学习状态合并(P)DFA
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