机器人世界杯仿真中基于树搜索的在线合作行为规划

Hidehisa Akiyama, S. Aramaki, T. Nakashima
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引用次数: 20

摘要

在本文中,我们提出了一种树搜索方法来生成和评估多智能体系统中的在线合作行为。对于状态-动作空间连续且要求实时性的任务,很难应用树搜索方法。然而,由于今天的计算资源变得更加强大,应用这种方法已经成为可能。我们将树搜索方法应用到机器人杯足球2D模拟中,并通过评价球队表现来分析其效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Cooperative Behavior Planning Using a Tree Search Method in the RoboCup Soccer Simulation
In this paper, we propose a tree search approach to generate and evaluate cooprative behavior online in multiagent systems. It was difficult to apply a tree search methodology to tasks that the state-action space is continuous and requires realtimeness. However, it has become possible to apply such an approach since the computational resources became more powerful today. We applied a tree search method to the Robo Cup soccer 2D simulation and analyzed its effect by evaluating the team performance.
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