Finite state automata and connectionist machines: A survey

Abstract

Work in the literature related to Finite State Automata (FSAs) and Neural Networks (NNs) is review. These studies have dealt with Grammatical Inference tasks as well as how to represent FSAs through a neural model. The inference of Regular Grammars through NNs has been focused either on the acceptance or rejection of strings generated by the grammar or on the prediction of the possible successor(s) for each character in the string. Different neural architectures using first and second order connections were adopted. In order to extract the FSA inferred by a trained net, several techniques have been described in the literature, which are also reported here. Finally, theoretical work about the relationship between NNs and FSAs is outlined and discussed.