Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Self-organised evolutionary neural networks: algorithms and applications
Highly parallel computaions
A new adaptive merging and growing algorithm for designing artificial neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improving Prediction Interval Quality: A Genetic Algorithm-Based Method Applied to Neural Networks
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Efficient continuous-time asymmetric hopfield networks for memory retrieval
Neural Computation
Expert Systems with Applications: An International Journal
An evolutionary artificial neural networks approach for breast cancer diagnosis
Artificial Intelligence in Medicine
ε - Optimal Stopping Time for Genetic Algorithms
Fundamenta Informaticae
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A learning algorithm for neural networks based on genetic algorithms is proposed. The concept leads in a natural way to a model for the explanation of inherited behavior. Explicitly we study a simplified model for a brain with sensory and motor neurons. We use a general asymmetric network whose structure is solely determined by an evolutionary process. This system is simulated numerically. It turns out that the network obtained by the algorithm reaches a stable state after a small number of sweeps. Some results illustrating the learning capabilities are presented.