Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System
arXiv:2606.26267v1 Announce Type: new Abstract: Rating systems such as Elo serve as the gold standard for matchmaking in competitive chess. However, they inherently suffer from response lag due to their exclusive reliance on match outcomes, neglecting the granular quality of gameplay. Nevertheless, incorporating move-by-move information into rating adjustments presents a significant challenge given the substantial noise and the vastness of the game-state space. To address this, we propose the Dr
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Computer Science > Artificial Intelligence arXiv:2606.26267 (cs) [Submitted on 24 Jun 2026] Title:Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System Authors:Tianyuan Zhou, Zhizheng Fu, Tianming Yang View a PDF of the paper titled Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System, by Tianyuan Zhou and 2 other authors View PDF HTML (experimental) Abstract:Rating systems such as Elo serve as the gold standard for matchmaking in competitive chess. However, they inherently suffer from response lag due to their exclusive reliance on match outcomes, neglecting the granular quality of gameplay.
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