标题： 集体智能优于个体才能：《英雄联盟》案例研究 显示英文标题

标题： Collective Intelligence Outperforms Individual Talent: A Case Study in League of Legends

摘要： 游戏环境是研究复杂人工智能系统中人类互动和行为的热门实验平台。 特别是在多人在线战术竞技场（MOBA）游戏中，个人在高度逼真的虚拟环境中合作，这些环境涉及实时战略决策以及在资源管理、信息收集与共享、团队协同和集体动态方面的权衡。 本文探讨了从一群个体的合作行为中涌现的集体智能是否超过了技能娴熟个体所表现出的个体智能。这些个体不一定擅长单人任务，但在有效参与协作问题解决时表现出色。 这一结论通过《英雄联盟》中的案例研究展示，研究使用机器学习算法和统计方法分析为同一目的收集的大规模数据。 通过系统地建模游戏特定指标以及新的跨游戏拓扑和图谱谱系度量合作互动的方法，我们展示了集体智能卓越性能的有力见解。 显示英文摘要

摘要： Gaming environments are popular testbeds for studying human interactions and behaviors in complex artificial intelligence systems. Particularly, in multiplayer online battle arena (MOBA) games, individuals collaborate in virtual environments of high realism that involves real-time strategic decision-making and trade-offs on resource management, information collection and sharing, team synergy and collective dynamics. This paper explores whether collective intelligence, emerging from cooperative behaviours exhibited by a group of individuals, who are not necessarily skillful but effectively engage in collaborative problem-solving tasks, exceeds individual intelligence observed within skillful individuals. This is shown via a case study in League of Legends, using machine learning algorithms and statistical methods applied to large-scale data collected for the same purpose. By modelling systematically game-specific metrics but also new game-agnostic topological and graph spectra measures of cooperative interactions, we demonstrate compelling insights about the superior performance of collective intelligence.