Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Evolving Turing Machines for Biosequence Recognition and Analysis
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Evolving Turing Machines from Examples
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
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
Does Chomsky complexity affect genetic programming computational requirements?
Proceedings of the South African Institute of Computer Scientists and Information Technologists Conference on Knowledge, Innovation and Leadership in a Diverse, Multidisciplinary Environment
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Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, a Turing machine which produces a solution algorithm is generated. The original problem is reduced to that of inducing an acceptor for a recursively enumerable language or a Turing machine transducer. This paper reports on a genetic programming system implemented to evolve Turing machine acceptors and transducers. Each element of the population is represented as a directed graph and graph crossover, mutation and reproduction are used to evolve each generation. The paper also presents a set of five acceptor and five transducer benchmark problems which can be used to test and compare different methodologies for generating Turing machines. The genetic programming system implemented evolved general solutions for all ten problems.