RoundTable: Investigating Group Decision-Making Mechanism in Multi-Agent Collaboration

• URL: http://arxiv.org/abs/2411.07161v1
• Date: Mon, 11 Nov 2024 17:37:47 GMT
• Title: RoundTable: Investigating Group Decision-Making Mechanism in Multi-Agent Collaboration
• Authors: Young-Min Cho, Raphael Shu, Nilaksh Das, Tamer Alkhouli, Yi-An Lai, Jason Cai, Monica Sunkara, Yi Zhang,
• Abstract summary: This study investigates the efficacy of Multi-Agent Systems in eliciting cross-agent communication and enhancing collective intelligence. By applying different voting rules in various environments, we find that moderate decision flexibility yields better outcomes.
• Score: 15.2119694237099
• License:
• Abstract: This study investigates the efficacy of Multi-Agent Systems in eliciting cross-agent communication and enhancing collective intelligence through group decision-making in a decentralized setting. Unlike centralized mechanisms, where a fixed hierarchy governs social choice, decentralized group decision-making allows agents to engage in joint deliberation. Our research focuses on the dynamics of communication and decision-making within various social choice methods. By applying different voting rules in various environments, we find that moderate decision flexibility yields better outcomes. Additionally, exploring the linguistic features of agent-to-agent conversations reveals indicators of effective collaboration, offering insights into communication patterns that facilitate or hinder collaboration. Finally, we propose various methods for determining the optimal stopping point in multi-agent collaborations based on linguistic cues. Our findings contribute to a deeper understanding of how decentralized decision-making and group conversation shape multi-agent collaboration, with implications for the design of more effective MAS environments.

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