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Agent-based simulation analysis for social norms

机译:基于Agent的社会规范仿真分析

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With existence of the social custom or norm, Naylor demonstrates a possibility of stable long-run equilibria of support for a strike in a labor market, and this implies that at least some individuals will behave cooperatively and hence the prisoners' dilemma could be escaped. In this paper, we develop an agent-based simulation system in which artificial adaptive agents have mechanisms of decision making and learning based on neural networks and genetic algorithms, and compare the result of our simulation analysis with that of the mathematical model by Naylor. Especially, while the Naylor model is based on rationality about maximization of individual utility, our agent-based simulation model employs adaptive behavior of agents; agents make decisions by trials and errors and they learn from experiences to make better decisions.
机译:有了社会习俗或规范,Naylor证明了长期稳定的劳动力市场罢工支持均衡的可能性,这意味着至少有些人会表现出合作精神,因此可以摆脱囚徒的困境。在本文中,我们开发了一种基于代理的仿真系统,其中人工自适应代理具有基于神经网络和遗传算法的决策和学习机制,并将我们的仿真分析结果与Naylor的数学模型进行了比较。尤其是,虽然Naylor模型基于个体效用最大化的合理性,但我们基于代理的仿真模型却采用了代理的自适应行为。代理商通过反复试验来做出决策,他们会从经验中学习以做出更好的决策。

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