Dungeon Dragon

Research on "Dungeon Dragon," encompassing the computational modeling and generation of Dungeons & Dragons (D&D) gameplay, focuses on improving AI agents' ability to participate in and manage D&D sessions. Current efforts leverage large language models (LLMs) and reinforcement learning (RL) to generate realistic dialogue, manage game state, and even act as Dungeon Masters (DMs), often incorporating techniques like multi-stage question decomposition and theory-of-mind modeling to enhance interaction quality. This research contributes to advancements in natural language processing, interactive storytelling, and AI-assisted game design, with potential applications in creating more engaging and dynamic gaming experiences.