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

TL;DR

This study demonstrates that collective intelligence in multiplayer online games like League of Legends can surpass individual skill, highlighting the power of cooperation and teamwork in complex strategic environments.

Contribution

The paper introduces new graph-based measures of cooperation and provides empirical evidence that collective intelligence outperforms individual talent in MOBA games.

Findings

Collective intelligence exceeds individual skill in game performance.

New topological measures effectively model cooperative interactions.

Machine learning confirms the superiority of group collaboration.

Abstract

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.