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AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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Information Sciences—Informatics and Computer Science: An International Journal - Special Issue on Quantum Computing and Neural Information Processing
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ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
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Selected Papers from the 5th European Conference on Artificial Evolution
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CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
Hierarchical BOA on random decomposable problems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Initial approaches to the application of islands-based parallel EDAs in continuous domains
Journal of Parallel and Distributed Computing - Special issue on parallel bioinspired algorithms
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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Evolutionary Computation
Diversity loss in general estimation of distribution algorithms
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
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ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
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ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
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ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
IEEE Transactions on Evolutionary Computation
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
Elitism-based compact genetic algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
On the convergence of a class of estimation of distribution algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
An evolutionary algorithm with guided mutation for the maximum clique problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Integrated feature and parameter optimization for an evolving spiking neural network
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Quantum-inspired evolutionary algorithms: a survey and empirical study
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Applied Soft Computing
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
NeuCube evospike architecture for spatio-temporal modelling and pattern recognition of brain signals
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
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ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
EDA-Based Scheduling of Users in the MIMO Multiple Access Channel
Wireless Personal Communications: An International Journal
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The quantum-inspired evolutionary algorithm (QEA) applies several quantum computing principles to solve optimization problems. In QEA, a population of probabilistic models of promising solutions is used to guide further exploration of the search space. This paper clearly establishes that QEA is an original algorithm that belongs to the class of estimation of distribution algorithms (EDAs), while the common points and specifics of QEA compared to other EDAs are highlighted. The behavior of a versatile QEA relatively to three classical EDAs is extensively studied and comparatively good results are reported in terms of loss of diversity, scalability, solution quality, and robustness to fitness noise. To better understand QEA, two main advantages of the multimodel approach are analyzed in details. First, it is shown that QEA can dynamically adapt the learning speed leading to a smooth and robust convergence behavior. Second, we demonstrate that QEA manipulates more complex distributions of solutions than with a single model approach leading to more efficient optimization of problems with interacting variables.