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A multi-agent learning model based on dynamic fuzzy logic

机译:基于动态模糊逻辑的多主体学习模型

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Machine learning is one of the key problems of artificial intelligence, and the agent learning has become an important branch of machine learning. One of the main characters of intelligence agent is that it can adapt to the unknown environment. The ability to learn is the key property of agent. Because the learning act of agent is dynamic and fuzzy, this paper uses the conception of dynamic fuzzy logic. First, it gives the conception of agent learning based on DFL. Then, it supplies a multi-agent learning model based on DFL, namely a multi-agent learning model planned on a whole. Furthermore, the paper validates that the model is an useful model by an example.
机译:机器学习是人工智能的关键问题之一,智能体学习已经成为机器学习的重要分支。智能代理的主要特征之一是它可以适应未知环境。学习能力是代理的关键属性。由于主体的学习行为是动态的和模糊的,因此本文采用动态模糊逻辑的概念。首先,它给出了基于DFL的代理学习的概念。然后,它提供了一种基于DFL的多智能体学习模型,即整体规划的多智能体学习模型。此外,本文通过一个实例验证了该模型是有用的模型。

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