Introduction to computer theory
Introduction to computer theory
Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Evolving deterministic finite automata using cellular encoding
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Evolving finite state transducers: some initial explorations
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
The induction of finite transducers using genetic programming
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Evolving accurate and compact classification rules with gene expression programming
IEEE Transactions on Evolutionary Computation
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This paper presents an alternative method for solving the problem of finite transducers using gene expression programming (GEP). Each individual in the GEP system represents a Mealy machine with outputs for each state. Be means of roulette-wheel sampling, individuals are chosen for the next generation and are put through a series of genetic operators which seek to change the mark-up of the individual to better fit the selection environment/ fitness sets. The system was tested with five problems to show its effectiveness and success at solving all of those problems.