Oops, Not Now: PEARL, a RAG-Based Support Agent for Gameplay and What Players Want from AI Help
AI-powered gameplay support agents hold promise for game-based learning, yet grounding generative models in structured game data remains an open challenge. We present PEARL (Parallel Education Agent for Reflection and Learning), a dual-component Retrieval-Augmented Generation (RAG) system that combines semantic knowledge retrieval with structural board-state matching to deliver contextualized scaffolding in Parallel, a puzzle game for learning parallel programming. PEARL operates on two input streams (natural language queries and board topology), retrieving both conceptual explanations of gameplay moves and peer-generated board states as evidence: capabilities unavailable to a standard La...
| Authors | Jiahong Li, Sai Siddartha Maram, Atieh Kashani et al. |
|---|---|
| Primary category | cs.HC |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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