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Literature Review Of Multi-Agent Debate For Problem-Solving

Published 29 May 2025 in cs.MA and cs.AI | (2506.00066v1)

Abstract: Multi-agent LLMs (MA-LLMs) are a rapidly growing research area that leverages multiple interacting language agents to tackle complex tasks, outperforming single-agent LLMs. This literature review synthesizes the latest research on agent profiles, communication structures, and decision-making processes, drawing insights from both traditional multi-agent systems and state-of-the-art MA-LLM studies. In doing so, it aims to address the lack of direct comparisons in the field, illustrating how factors like scalability, communication structure, and decision-making processes influence MA-LLM performance. By examining frequent practices and outlining current challenges, the review reveals that multi-agent approaches can yield superior results but also face elevated computational costs and under-explored challenges unique to MA-LLM. Overall, these findings provide researchers and practitioners with a roadmap for developing robust and efficient multi-agent AI solutions.

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