CueTip: An Interactive and Explainable Physics-aware Pool Assistant
This addresses the need for interpretable AI assistants in sports coaching, though it is incremental as it builds on existing physics simulators and language models.
The paper tackles the problem of creating an interactive and explainable coaching assistant for pool/billiards by combining a natural-language interface with physics-aware reasoning and expert-grounded explanations, resulting in a system that maintains or improves win rates while providing reliable, contextual assistance.
We present an interactive and explainable automated coaching assistant called CueTip for a variant of pool/billiards. CueTip's novelty lies in its combination of three features: a natural-language interface, an ability to perform contextual, physics-aware reasoning, and that its explanations are rooted in a set of predetermined guidelines developed by domain experts. We instrument a physics simulator so that it generates event traces in natural language alongside traditional state traces. Event traces lend themselves to interpretation by language models, which serve as the interface to our assistant. We design and train a neural adaptor that decouples tactical choices made by CueTip from its interactivity and explainability allowing it to be reconfigured to mimic any pool playing agent. Our experiments show that CueTip enables contextual query-based assistance and explanations while maintaining the strength of the agent in terms of win rate (improving it in some situations). The explanations generated by CueTip are physically-aware and grounded in the expert rules and are therefore more reliable.