Abstract
This paper reports on the results of a preliminary study conducted to evaluate genetic programming (GP) as a means of evolving finite state transducers. A genetic programming system representing each individual as a directed graph was implemented to evolve Mealy machines. Tournament selection was used to choose parents for the next generation and the reproduction, mutation and crossover operators were applied to the selected parents to create the next generation. The system was tested on six standard Mealy machine problems. The GP system was able to successfully induce solutions to all six problems. Furthermore, the solutions evolved were human-competitive and in all cases the minimal transducer was evolved.
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Naidoo, A., Pillay, N. (2007). The Induction of Finite Transducers Using Genetic Programming. In: Ebner, M., O’Neill, M., Ekárt, A., Vanneschi, L., Esparcia-Alcázar, A.I. (eds) Genetic Programming. EuroGP 2007. Lecture Notes in Computer Science, vol 4445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71605-1_35
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DOI: https://doi.org/10.1007/978-3-540-71605-1_35
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