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In this paper, we validate whether the network modularity can emerge, and the evolution performance can be improved by varying the environment or evolution process under a more freeform artificial evolution. Previous studies have demonstrated that the modular structure naturally arisen as a response of the variations on environment and selection process, however, since the models they used were relatively...
We propose a pure topological recurrent networks controller, which has random binary connections in hidden layer, and all hidden neurons are activated by sinusoidal functions. A direct graph encoding method and four genetic operators are implemented for using genetic programming to train this controller. Firstly, its feasibility and efficiency were validated by a pair of function approximation experiments,...
We propose a pure topological recurrent network controller for satellite attitude control, which has random binary connections in hidden layer, and all hidden neurons are activated by sinusoidal functions. A direct graph encoding method and four genetic operators are implemented for using genetic programming to train this controller. Moreover, a simulated small satellite which equipped with three...
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