This paper presents a deep reinforcement learning AI that uses sound as the input on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In this work, an AI that only uses sound as the input is called blind AI. While state-of-the-art AIs rely mostly on visual or structured observations provided by their environments, learning to play games from only sound is still new and thus challenging. We propose different approaches to process audio data and use the Proximal Policy Optimization algorithm for our blind AI. We also propose to use our blind AI in evaluation of sound designs submitted to the competition and define three metrics for this task. The experimental results show the effectiveness of not only our blind AI but also the proposed three metrics.
翻译:本文介绍了一个深入强化学习的AI,它使用声音作为2022年IEEECOG DareFightingICE 比赛DareFightingICE平台上的投入。在这项工作中,只使用声音作为输入内容的AI被称为盲人AI。尽管最先进的AI主要依赖环境提供的视觉或结构化观测,但从声音中学习玩游戏仍然很新,因此具有挑战性。我们提出了处理音频数据的不同方法,并为我们的盲人AI使用Proximal政策优化算法。我们还提议使用我们的盲人AI来评估提交给竞争的音响设计,并为这项任务确定三个衡量标准。实验结果不仅显示了我们的盲人AI的有效性,而且显示了拟议的三个衡量标准的有效性。