  This paper presents a deep reinforcement learning agent (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 two metrics for this task. The
experimental results show the effectiveness of not only our blind AI but also
the proposed two metrics.
