On the alleviation of the problem of local minima in back-propagation
Proceedings of second world congress on Nonlinear analysts
Swarm intelligence
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Journal of Global Optimization
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
Parallel evolutionary training algorithms for “hardware-friendly“ neural networks
Natural Computing: an international journal
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
A Trigonometric Mutation Operation to Differential Evolution
Journal of Global Optimization
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
An evolutionary game based particle swarm optimization algorithm
Journal of Computational and Applied Mathematics
An adaptive policy gradient in learning Nash equilibria
Neurocomputing
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Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.