Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System
Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System
加速国际象棋技能评估：一种漂移扩散增强型 Elo 等级分系统
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. 摘要： 像 Elo 这样的等级分系统是竞技国际象棋匹配赛事的黄金标准。然而，由于它们仅依赖比赛结果，忽略了对局过程中的细粒度质量，因此在本质上存在响应滞后的问题。
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 Drift-Diffusion-Enhanced Elo Rating System (DD-Elo), a novel skill assessment framework inspired by the drift diffusion model (DDM) from cognitive neuroscience. 尽管如此，考虑到巨大的噪声和广阔的游戏状态空间，将逐手棋的信息纳入等级分调整中是一项重大挑战。为了解决这个问题，我们提出了漂移扩散增强型 Elo 等级分系统（DD-Elo），这是一个受认知神经科学中漂移扩散模型（DDM）启发的新型技能评估框架。
By modeling skill expression as a decision-making process, our model integrates move-level data to capture rapid skill fluctuations. We provide a rigorous mathematical derivation proving that DD-Elo maintains a bounded deviation from the traditional Elo system, ensuring theoretical alignment. 通过将技能表现建模为一个决策过程，我们的模型整合了棋步层面的数据，以捕捉技能的快速波动。我们提供了严谨的数学推导，证明了 DD-Elo 与传统 Elo 系统相比保持了有限的偏差，从而确保了理论上的一致性。
Extensive experiments demonstrate that DD-Elo adapts to skill changes faster than Elo. Our findings suggest that DD-Elo offers an explainable, highly responsive, and backward-compatible solution for chess rating ecosystems. The implementation code is publicly available at this URL. 广泛的实验表明，DD-Elo 对技能变化的适应速度比 Elo 更快。我们的研究结果表明，DD-Elo 为国际象棋等级分生态系统提供了一种可解释、高响应且向后兼容的解决方案。实现代码已在指定网址公开。
Paper Details:
- Authors: Tianyuan Zhou, Zhizheng Fu, Tianming Yang
- Subject: Artificial Intelligence (cs.AI)
- arXiv ID: 2606.26267
- Date: 24 Jun 2026
论文详情：
- 作者： Tianyuan Zhou, Zhizheng Fu, Tianming Yang
- 学科： 人工智能 (cs.AI)
- arXiv ID: 2606.26267
- 日期： 2026年6月24日