Evolutionary learning in agent-based modeling
Evolutionary learning in agent-based modeling
复制标题
基于主体的建模中的进化学习
DOI：
10.1007/978-1-4757-3554-3_14
复制
发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Shingo Takahashi
中科院分区：
文献类型：
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作者：
Shingo Takahashi
本文提出了一种基于智能体建模的进化学习通用模型。一般模型的核心概念在于内部模型原理和进化方式的主体内部模型的相互学习。本文以网络型动态超对策为模型，描述了多智能体环境下的进化学习过程，并提出了一种用遗传算法进行仿真的网络型动态超对策。本文给出的实验结果给出了有效推进学习过程的一些必要条件。
This paper develops a general model for evolutionary learning in agent-based modeling. The central concepts of the general model lie in internal model principle and mutual learning of agent’s internal models in an evolutionary way. This paper particularly presents network-type dynamic hypergame as a model to describe an evolutionary learning process in multi-agent situation and a simulation method by genetic algorithm to perform a network-type dynamic hypergame. The experimental results given in this paper show some requisite conditions to progress the learning process effectively.