Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Information Sciences—Intelligent Systems: An International Journal
A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Multi-agent oriented constraint satisfaction
Artificial Intelligence
An Adaptive Evolutionary Algorithm for Numerical Optimization
SEAL'96 Selected papers from the First Asia-Pacific Conference on Simulated Evolution and Learning
The Quantum Evolutionary Programming
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Algorithms for quantum computation: discrete logarithms and factoring
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
A multiagent genetic algorithm for global numerical optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Expert Systems with Applications: An International Journal
Quantum-inspired evolutionary algorithms: a survey and empirical study
Journal of Heuristics
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In this paper, a novel kind of algorithm, multiagent quantum evolutionary algorithm (MAQEA), is proposed based on multiagent, evolutionary programming and quantum computation. An agent represents a candidate solution for optimization problem. All agents are presented by quantum chromosome, whose core lies on the concept and principles of quantum computing, live in table environment. Each agent competes and cooperates with its neighbors in order to increase its competitive ability. Quantum computation mechanics is employed to accelerate evolution process. The result of experiments shows that MAQEA has a strong ability of global optimization and high convergence speed.