Learning deterministic finite automata with a smart state labeling evolutionary algorithm

@article{Lucas2005LearningDF,
  title={Learning deterministic finite automata with a smart state labeling evolutionary algorithm},
  author={Simon M. M. Lucas and T. Jeff Reynolds},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2005},
  volume={27},
  pages={1063-1074}
}
  • S. Lucas, T. J. Reynolds
  • Published 1 July 2005
  • Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a deterministic finite automaton (DFA) from a training set of labeled strings is a hard task that has been much studied within the machine learning community. It is equivalent to learning a regular language by example and has applications in language modeling. In this paper, we describe a novel evolutionary method for learning DFA that evolves only the transition matrix and uses a simple deterministic procedure to optimally assign state labels. We compare its performance with the… 

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