{"ID":2899394,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.02170","arxiv_id":"2507.02170","title":"Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System","abstract":"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.","short_abstract":"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 cal...","url_abs":"https://arxiv.org/abs/2507.02170","url_pdf":"https://arxiv.org/pdf/2507.02170v1","authors":"[\"Adam Kostka\",\"Jarosław A. Chudziak\"]","published":"2025-07-02T21:53:44Z","proceeding":"cs.MA","tasks":"[\"cs.MA\"]","methods":"[\"Large Language Model\"]","has_code":false}