Robocup2D项目中Agent2D底层动作链机制的分析优化
发布时间：2018-11-28 14:22
【摘要】：在Robo Cup2D仿真足球项目中,Agent2D是我国使用最为广泛的球队底层之一。仿真平台中数据传输的噪声干扰及代码自身动作链机制不完整等因素,导致采用Agent2D底层的球队在应对不同的队伍时,存在着适应能力不足的缺点,影响了球队的整体能力。该论文引入了动作修正参数,利用强化学习的手段对动作链机制进行优化,使Agent底层球队在面对不同风格的对手时可以选择更加有效的动作执行,以此来提升球队的适应性。仿真实验证明,此法具有一定效果。
[Abstract]:In the Robo Cup2D soccer simulation project, Agent2D is one of the most widely used teams in our country. The noise interference of data transmission in the simulation platform and the incomplete mechanism of the code itself result in the deficiency of adaptive ability of the teams using Agent2D in dealing with different teams, which affects the overall ability of the team. This paper introduces the motion correction parameters and optimizes the action chain mechanism by means of reinforcement learning so that the Agent team can choose more effective action execution in the face of different styles of opponents in order to improve the adaptability of the team. The simulation results show that this method has certain effect.
【作者单位】： 信息工程大学理学院;信息工程大学指挥军官基础教育学院;安徽工业大学计算机学院;
【分类号】：TP242
，
本文编号：2363109
[Abstract]:In the Robo Cup2D soccer simulation project, Agent2D is one of the most widely used teams in our country. The noise interference of data transmission in the simulation platform and the incomplete mechanism of the code itself result in the deficiency of adaptive ability of the teams using Agent2D in dealing with different teams, which affects the overall ability of the team. This paper introduces the motion correction parameters and optimizes the action chain mechanism by means of reinforcement learning so that the Agent team can choose more effective action execution in the face of different styles of opponents in order to improve the adaptability of the team. The simulation results show that this method has certain effect.
【作者单位】： 信息工程大学理学院;信息工程大学指挥军官基础教育学院;安徽工业大学计算机学院;
【分类号】：TP242
，
本文编号：2363109
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