2024/11/11 by Youngmin Cho, Raphael Shu, Cho, Young-Min +13
Business, Management and Accounting · Psychology · #Artificial Intelligence (cs.AI) #Business Strategy and Innovation #Collaboration in agile enterprises #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Team Dynamics and Performance
paper · pdf · doi:10.48550/arxiv.2411.07161
openalex publication_date 2024/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Effective group decision-making is critical in Multi-Agent Systems (MAS). Yet, how different mechanisms for reaching consensus impact collaboration quality and efficiency remains understudied. We conduct a systematic study on group decision-making mechanisms in a decentralized setting. Through controlled experiments, we analyze how different voting rules affect decision quality and efficiency in a multi-round collaboration. Results reveal that majority voting often cause inefficient collaboration due to its strict acceptance criteria. At the extreme, unanimous voting gives 87% lower initial performance than the best-performing method. Our qualitative analysis of cross-agent communication shows that messages become longer and more repetitive over time: while message length increases by 84%, similarity to the previous round increases to 90%. Based on these insights, language-based early stopping methods make the performance 13% closer to oracle while reducing rounds by 50%. Our findings highlight the crucial role of group decision-making in optimizing MAS collaboration.