多智能体模型中神经网络的连续自适应

Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290) Pub Date : 2002-08-07 DOI:10.1109/IJCNN.2002.1007527

H. Ishibuchi, T. Seguchi

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引用次数: 2

摘要

本文研究了非合作重复市场选择博弈中神经网络对环境渐变和突变的适应性。将神经网络作为agent的决策系统进行迭代博弈。训练数据是由神经网络在每一轮游戏中连续生成的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Successive adaptation of neural networks in a multi-agent model

This paper examines the adaptability of neural networks to gradual and sudden changes in the environment of a non-cooperative repeated market selection game. Neural networks are used as decision-making systems of agents for iterative game playing. Training data are successively generated from each round of our game by the neural networks.

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Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)

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