Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic Reinforcement Learning for Neurocontrol Problems
Machine Learning - Special issue on genetic algorithms
Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Efficient reinforcement learning through symbiotic evolution
Machine Learning - Special issue on reinforcement learning
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Robust non-linear control through neuroevolution
Robust non-linear control through neuroevolution
Co-evolving recurrent neurons learn deep memory POMDPs
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Searching for diverse, cooperative populations with genetic algorithms
Evolutionary Computation
GA-based fuzzy reinforcement learning for control of a magneticbearing system
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic reinforcement learning through symbiotic evolution forfuzzy controller design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A recurrent fuzzy-neural model for dynamic system identification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Prediction and identification using wavelet-based recurrent fuzzy neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An ART-based fuzzy adaptive learning control network
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Genetic algorithm for the design of a class of fuzzy controllers: an alternative approach
IEEE Transactions on Fuzzy Systems
Fuzzy wavelet networks for function learning
IEEE Transactions on Fuzzy Systems
Self-constructing fuzzy neural network speed controller for permanent-magnet synchronous motor drive
IEEE Transactions on Fuzzy Systems
Combination of online clustering and Q-value based GA for reinforcement fuzzy system design
IEEE Transactions on Fuzzy Systems
Recurrent neuro-fuzzy networks for nonlinear process modeling
IEEE Transactions on Neural Networks
A recurrent self-organizing neural fuzzy inference network
IEEE Transactions on Neural Networks
On the dynamical modeling with neural fuzzy networks
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Learning and tuning fuzzy logic controllers through reinforcements
IEEE Transactions on Neural Networks
Neural networks designed on approximate reasoning architecture and their applications
IEEE Transactions on Neural Networks
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This paper proposes a recurrent wavelet-based neuro-fuzzy system (RWNFS) with a reinforcement group cooperation-based symbiotic evolution (R-GCSE) for solving various control problems. The R-GCSE is different from the traditional symbiotic evolution. In the R-GCSE method, a population is divided to several groups. Each group formed by a set of chromosomes represents a fuzzy rule and cooperates with other groups to generate better chromosomes by using the proposed elite-based compensation crossover strategy (ECCS). In this paper, the proposed R-GCSE is used to evaluate numerical control problems. The performance of the R-GCSE in the simulations is excellent compared with other existing models.