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Titlebook: Bio-Inspired Computational Intelligence and Applications; International Confer Kang Li,Minrui Fei,Shiwei Ma Conference proceedings 2007 Spr

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An Agent Reinforcement Learning Model Based on Neural Networksesigns the agent reinforcement learning based on neural networks. By the simulation experiment of agent’s bid price in Multi-Agent Electronic Commerce System, validated the Agent Reinforcement Learning Algorithm Based on Neural Networks has very good performance and the action impending ability.
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Application of the Agamogenetic Algorithm to Solve the Traveling Salesman Problemamogenetic operator R-Edge and one mutation operator NI-Dot are given by introducing the conception of the relative distance between cities. The validity of the AGA to solve the traveling salesman problem is shown by simulative experiments.
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https://doi.org/10.1007/978-3-642-45817-0or dynamic modification of the population’s dimensionality. A mathematical example was applied to evaluate this proposed approach. The experiment results suggested that this proposed approach is feasible, correct and valid.
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A Novel Neural Network Based Reinforcement Learningthe validity of ART2-RL. As the complexity of the simulation increased, the result shows that the number of collision between robot and obstacles is effectively decreased; the novel neural network model provides significant improvement in the space measurement of reinforcement learning.
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Parameter Identification of Bilinear System Based on Genetic Algorithm. Through a simulation study to an MIMO bilinear system, good results can still be got. In the last section, the paper describes that a hybrid GA, the combination of Genetic Algorithm and nonlinear Least Square, was developed to identify bilinear system structure and parameters simultaneously.
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