发表机构
Technion; Research Institute for Symbolic Computation, Johannes Kepler Universität Linz; Ghent University; Toronto Metropolitan University（以色列理工学院; 林茨约翰内斯·开普勒大学符号计算研究所; 根特大学; 多伦多都会大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一组用于评估人工智能数学技能的基本数学常数公式，含已知证明暂加密及未证明两类问题，旨在观察人工智能在这些问题上的表现。
AI 中文摘要
为帮助评估当前人工智能系统的数学技能，我们提出了一组关于基本数学常数的公式。这些问题对人工智能评估很有吸引力，因为它们具体且能以任意精度进行数值检验，但证明它们可能需要非平凡的数学知识。诸如π、e、卡塔兰常数和黎曼ζ函数的特殊值等数学常数，几个世纪以来一直吸引着数学家。寻找评估数学常数的公式产生了该领域一些最优美的数学成果。我们提供的列表包含两类问题：作者已知证明但在初始短时期内加密的公式，以及尚未证明的公式。我们好奇人工智能在这两种情况下的成果。
英文摘要
To help evaluate the mathematical skills of current AI systems, we present a set of formulas for fundamental mathematical constants. These problems are attractive for AI evaluation because they are concrete and can be checked numerically to arbitrary precision, yet proving them may require non-obvious mathematics. Mathematical constants such as $π$, $e$, Catalan's constant, and special values of the Riemann zeta function have fascinated mathematicians for centuries. The search for formulas evaluating mathematical constants has produced some of the most beautiful mathematics in the field, especially in cases that yield irrationality proofs or fast convergence rates. Ramanujan's legacy is emblematic of this tradition. The list we provide contains two types of problems: formulas whose proofs are known to the authors but will remain encrypted for a short initial period; and formulas that are not yet proven. We are curious to see the achievements of AI in both cases.
CommentsPlease submit solutions at https://www.ramanujanmachine.com/ramanujan-challenge/
