A Two-Tier DRL and LLM-Based Agent System for Enhancing Fighting Game Enjoyability
Developing a two-tier agent (TTA) system that enhances player enjoyment in Street Fighter II using deep reinforcement learning (DRL) and a Large Language Model Hyper-Agent, which dynamically selects suitable DRL opponents based on player data and feedback.