Derivation And Optimization Algorithm Of Automata Combination

Grammar inference has received more and more attention due to its wide application. This paper is concerned with the combination of several optimal algorithms with this research field.In chapter 1, we begin with some results of the grammar inference using neural networks and then a construction method is proposed to induce the fuzzy finite state automaton. This algorithm recovers the absence of the empiric in the case of the fixed-topology network and generates an optimal topology automatically. We end this chapter with some problems in the future.In chapter 2, We present an evolution strategy to infer fuzzy finite-state automaton, The fitness function of a generated automaton with respect to the set of examples of a fuzzy language, the representation of the transition and the output of the automaton and the simple mutation operators that work on these representations are given. Results are reported on the inference of a fuzzy language.Evolution algorithm and gradient decent algorithm are combined to the grammar inference. First use an evolution algorithm to infer the automaton from examples of a language and then encode the generated automaton to a network. The expected automaton is finally extracted from the trained network.