We report on discovering new record-breaking Condorcet domains on $n=10$ and n=11 alternatives, challenging long-standing voting theory results. Our work presents new records with sizes of 1082 (previous record 1069) for n=10 and 2349 (previous record 2324) for $n=11$, which appear sporadic and do not fit into the existing alternating schema discovered in 1996. While the method used to discover these domains was inspired by the application of value functions in reinforcement learning, a subcategory of artificial intelligence, the current version of the method is somewhat ad-hoc and unstable. Therefore, we will not expound on the search method in this paper. Instead, we outline the key components that contribute to the success of our approach. We will also discuss the theoretical implications of our findings and explore the structure of the new Condorcet domains, raising several open questions related to them. Our results contribute to the ongoing investigation of Condorcet domains and their mathematical properties, potentially demonstrating the power of artificial intelligence-inspired problem-solving methods in advancing mathematical research.
翻译:我们的工作为n=10和2349的N=10和2349的N=10和N=10(前记录1069)(前记录2324)(前记录2324)提供了新记录,这些记录看起来零星,并不符合1996年发现的现有交替模式。 发现这些域所使用的方法受到在强化学习中应用价值功能的启发,这是人工智能的子类别,而目前采用的方法是某种临时和不稳定的。因此,我们不会在本文件中阐述搜索方法。相反,我们将概述有助于我们方法成功的关键组成部分。我们还将讨论我们发现的结果的理论影响,并探讨新的Condorcet域的结构,提出与它们有关的几个开放问题。我们的结果有助于对Condorcet域及其数学特性进行持续调查,可能显示人造情报激发的问题解决方法在推进数学研究方面的力量。</s>