论文标题
微疗法：在不确定性和混乱下玩微型
microPhantom: Playing microRTS under uncertainty and chaos
论文作者
论文摘要
该竞赛论文介绍了Microphantom，这是一个机器人播放微型并参加了2020年的AI竞赛。 Microphantom是基于我们以前的机器人Poadaptive，该机器人赢得了2018年和2019年AI竞赛的部分可观察到的曲目。在本文中，我们通过基于约束编程和决策理论的结合来解决单位生产问题，将重点放在不确定性下的决策上。我们表明，使用我们的方法来确定要训练的单位可显着提高与部分可观察到的第二好的微型机器人的获胜率。我们还表明，我们的方法在混乱的环境中具有弹性，仅效率损失很小。为了允许复制性并促进进一步的研究，可用的微观量源代码以及它使用的约束编程工具包。
This competition paper presents microPhantom, a bot playing microRTS and participating in the 2020 microRTS AI competition. microPhantom is based on our previous bot POAdaptive which won the partially observable track of the 2018 and 2019 microRTS AI competitions. In this paper, we focus on decision-making under uncertainty, by tackling the Unit Production Problem with a method based on a combination of Constraint Programming and decision theory. We show that using our method to decide which units to train improves significantly the win rate against the second-best microRTS bot from the partially observable track. We also show that our method is resilient in chaotic environments, with a very small loss of efficiency only. To allow replicability and to facilitate further research, the source code of microPhantom is available, as well as the Constraint Programming toolkit it uses.
