A novel population initialization method for accelerating evolutionary algorithms
Computers & Mathematics with Applications
Opposition versus randomness in soft computing techniques
Applied Soft Computing
Oppositional target domain estimation using grid-based simulation
Applied Soft Computing
Solving large scale optimization problems by opposition-based differential evolution (ODE)
WSEAS Transactions on Computers
Investigating in scalability of opposition-based differential evolution
SMO'08 Proceedings of the 8th conference on Simulation, modelling and optimization
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Opposition based initialization in particle swarm optimization (O-PSO)
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Free search differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Center-based sampling for population-based algorithms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolutionary algorithm sandbox: a web-based graphical user interface for evolutionary algorithms
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Oppositional biogeography-based optimization
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization of neuro-fuzzy system parameters for diagnosis of cardiac disease
Proceedings of the 12th annual conference on Genetic and evolutionary computation
CODEQ: an effective metaheuristic for continuous global optimisation
International Journal of Metaheuristics
Particle swarm optimization with opposition-based disturbance
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
A differential evolution based neural network approach to nonlinear system identification
Applied Soft Computing
Diversity analysis of opposition-based differential evolution: an experimental study
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Brief paper: An improved differential evolution algorithm for the task assignment problem
Engineering Applications of Artificial Intelligence
Knowledge of opposite actions for reinforcement learning
Applied Soft Computing
Opposition-based artificial bee colony algorithm
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A direct optimization approach to the P300 speller
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Opposition-based learning in compact differential evolution
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Enhancing particle swarm optimization using generalized opposition-based learning
Information Sciences: an International Journal
Classification of benign and malignant masses based on Zernike moments
Computers in Biology and Medicine
Improving differential evolution algorithm by synergizing different improvement mechanisms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Generalised opposition-based differential evolution: an experimental study
International Journal of Computer Applications in Technology
An intuitive distance-based explanation of opposition-based sampling
Applied Soft Computing
An heterogeneous particle swarm optimizer with predator and scout particles
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
An opposition-based chaotic GA/PSO hybrid algorithm and its application in circle detection
Computers & Mathematics with Applications
Advances in differential evolution for solving multiobjective optimization problems
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Investigating the application of opposition concept to colonial competitive algorithm
International Journal of Bio-Inspired Computation
Journal of Parallel and Distributed Computing
A hybrid algorithm for artificial neural network training
Engineering Applications of Artificial Intelligence
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Fast opposite weight learning rules with application in breast cancer diagnosis
Computers in Biology and Medicine
Teaching learning opposition based optimization for the location of median line in 3-d space
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Triple and quadruple comparison-based interactive differential evolution and differential evolution
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
A new design method using opposition-based BAT algorithm for IIR system identification problem
International Journal of Bio-Inspired Computation
Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm
Computer Methods and Programs in Biomedicine
Engineering Applications of Artificial Intelligence
Hardware opposition-based PSO applied to mobile robot controllers
Engineering Applications of Artificial Intelligence
A modified harmony search method for wind generator design
International Journal of Bio-Inspired Computation
Quadratic interpolation based orthogonal learning particle swarm optimization algorithm
Natural Computing: an international journal
Survey A review of opposition-based learning from 2005 to 2012
Engineering Applications of Artificial Intelligence
An improved diversity-guided particle swarm optimisation for numerical optimisation
International Journal of Computing Science and Mathematics
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Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions are the foundation of this new approach. Examples are provided. Possibilities for extensions of existing learning algorithms are discussed. Preliminary results are provided.