A Deep Reinforcement Learning Agent for Sound-Based Fighting Games

We present the agent we developed for the 2024 DareFightingICE competition that integrates advanced audio encoders, deep reinforcement learning, and hard-coded rules to improve the agent's behavior for one specific, rarely used attack. The integration of hard-coded rules with our 1D-CNN encoder let our agent outperform the 2023 DareFightingICE AI winners (Pythunder and CAS). Our agent achieved second place in the competition, being the only top-ranking submission using machine learning, while the other entries implemented scripted strategies. Despite its strengths, our entry can be defeated by analyzing its favorite moves. We plan to enhance the audio encoders, refine long-term planning strategies, and optimize training methods to narrow the gap between our entry and the other top entries.