多智能体捕食-食饵问题中的合作行为研究

Duo Zhao, Wei-dong Jin
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引用次数: 6

摘要

多智能体系统的一个重要研究内容是具有共同目标的智能体之间的合作行为的发展。本文研究了一个捕食者-猎物问题的例子,其中四个捕食者代理使用强化学习方法,试图共同实现包围一个猎物代理的任务。首先,描述了捕食者智能体和被捕食者智能体的结构、状态感知能力、动作学习方法和动作选择机制;接下来,我们研究了多智能体系统中捕食者-猎物问题中智能体之间的两种合作行为机制。最后,通过对捕食者-猎物问题的模拟,证明了合作行为的智能体优于没有合作行为的智能体,并给出了相应的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The study of cooperative behavior in predator-prey problem of multi-agent systems
An important study in multi-agent systems is the development of cooperative behavior between agents that have a shared goal. In this paper, an example of the predator-prey problem is studied in which four predator agents, using the reinforcement learning method, in an attempt to collectively achieve the task of surrounding one prey agent. First, we describe the structure of the predator agents and the prey agent with their state sensing capability, the action learning method and the action choosing mechanism. Next we study two cooperative behavior mechanisms between agents of multi-agent systems in predator-prey problem. Finally, we demonstrate that cooperative agents outperform agents without cooperative behavior according to simulations of the predator-prey problem and display the corresponding experimental results.
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