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Decision-Making and Tactical Behavior with Potential Fields

机译:具有潜在领域的决策和战术行为

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Using potential-fields is a seldomly used technique in RoboCup scenarios. The existing approaches mainly concentrate on world state representation on single actions such as a kick. In this paper we will show how to apply potential fields to assist fast and precise decisions in an easy and intuitive way. We go beyond the existing approaches in using potential fields to determine all possible player actions, basic and advanced tactics an also general player behaviors. To ensure fast computing we mainly use basic mathematical computation for potential field related calculations. This gives us the advantage of both determining and understanding player actions. Therefore, integrating future features such as a complex online coach and progressive localization methods will be easier. We implemented the approach in our team Bremen University Goal Seekers (BUGS) and tested it in numerous games against other simulation league teams. The results show that CPU-time of making a decision per team has been decreased significantly. This is a crucial improvement for calculations in time-critical environments.
机译:使用潜在字段是Robocup方案中的一个很少使用的技术。现有方法主要集中在世界州代表上的单一行动,如踢球。在本文中,我们将展示如何应用潜在的领域以简单而直观的方式帮助快速和精确的决策。我们超出了现有的使用潜在领域的方法,以确定所有可能的玩家动作,基本和高级策略也是一般玩家行为。为了确保快速计算,我们主要使用基本数学计算来进行潜在的场相关计算。这为我们提供了确定和理解玩家行为的优势。因此,整合未来的功能,如复杂的在线教练和渐进式定位方法将更容易。我们在我们的团队中实施了我们的队伍大学的方法,并在众多对阵其他模拟联盟队伍中测试了它。结果表明,每支球队决策的CPU时间显着下降。这是对时间关键环境计算的重要改进。

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