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Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLMs (arxiv.org)
5 points by PaulHoule on Jul 19, 2025 | hide | past | pdf | discuss on HN

In plain words: A team of AI agents keeps a shared memory of past work, reasons step by step, and works out what its teammates know, then coordinates through messages to solve problems. In a product-development case study, it boosted performance and adaptability over the usual approach.

Abstract · Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System

This paper explores the integration of advanced Multi-Agent Systems (MAS) techniques to develop a team of agents with enhanced logical reasoning, long-term knowledge retention, and Theory of Mind (ToM) capabilities. By uniting these core components with optimized communication protocols, we create a novel framework called SynergyMAS, which fosters collaborative teamwork and superior problem-solving skills. The system's effectiveness is demonstrated through a product development team case study, where our approach significantly enhances performance and adaptability. These findings highlight SynergyMAS's potential to tackle complex, real-world challenges.

Adam Kostka, Jarosław A. Chudziak
arXiv:2507.02170 · cs.MA · submitted Jul 2, 2025
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