论文标题
蒙特卡洛树搜索基于战术机动
Monte Carlo Tree Search Based Tactical Maneuvering
论文作者
论文摘要
在本文中，我们探讨了基于蒙特卡洛树搜索（MCT）在线框架同时移动的应用，以在两架无人飞机之间进行战术操纵。与其他技术相比，MCT可以在远距离上进行有效的搜索，并使用自我播放来在当前状态下选择最佳动作，同时考虑对手飞机策略。我们在MCT中探索不同的算法选择，并在模拟的2D战术操作应用中以数字方式演示框架。
In this paper we explore the application of simultaneous move Monte Carlo Tree Search (MCTS) based online framework for tactical maneuvering between two unmanned aircrafts. Compared to other techniques, MCTS enables efficient search over long horizons and uses self-play to select best maneuver in the current state while accounting for the opponent aircraft tactics. We explore different algorithmic choices in MCTS and demonstrate the framework numerically in a simulated 2D tactical maneuvering application.
