Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolving cellular automata to perform computations: mechanisms and impediments
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
Genetic Programming IV: Routine Human-Competitive Machine Intelligence
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Inverse design of cellular automata by genetic algorithms: an unconventional programming paradigm
UPP'04 Proceedings of the 2004 international conference on Unconventional Programming Paradigms
Parameter tuning of evolutionary reactions systems
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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It is an unconventional computation approach to evolve solutions instead of calculating them. Although using evolutionary computation in computer science dates back to the 1960s, using an evolutionary approach to program other algorithms is not that well known. In this paper a genetic algorithm is used to evolve behavior in cellular automata. It shows how this approach works for different topologies and neighborhood shapes. Some different one dimensional neighborhood shapes are investigated with the genetic algorithm and yield surprisingly good results.