強化学習による人間のスキル開発を加速するAIコーチング
AI Coaching for Accelerating Human Skill Development with Reinforcement Learning
AIコーチが人間の運動スキル習得を加速する方法を研究し、学習者の能力に合わせた戦略的支援と段階的介入を行う強化学習フレームワークを提案。ドローン競技のユーザー実験で学習効果の向上を実証した。
著者: Wei Wang, Enlin Gu, Antonio Loquercio, Haimin Hu, Rahul Mangharam
分類: cs.RO, cs.AI, cs.HC
原文アブストラクト
AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This paper studies how an embodied AI agent can act as a coach that accelerates human motor-skill development. We argue that effective coaching requires strategic scaffolding and stepping back that are aligned with the learner's capability, allowing productive failures that drive learning. We formalize the interactive AI coaching process as a non-cooperative dynamic game in which the learner optimizes task performance while the coach targets the learner's independent competence. Building on this formalism, we develop a reinforcement learning framework combining adaptive shared control with probabilistic models of the coach's causal influence on skill evolution, enabling tractable training of coaching policies. A comprehensive user study (N=33) on first-person-view drone racing shows significant gains in human learning outcomes over state-of-the-art AI coaching baselines.