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Large Language Models (LLMs) are increasingly utilized in multi-agent systems (MAS) to enhance collaborative problem-solving and interactive reasoning.
Concurrency control in distributed database systems
Philip A. Bernstein and Nathan Goodman · 1986
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Distributed problem solving and planning
Edmund H. Durfee · 1991
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Towards flexible teamwork
Milind Tambe · 1997
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Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Jacques Ferber · 1999
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Industrial and Practical Applications of DAI
H. Van Dyke Parunak · 1999
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Multiagent systems: A survey from a machine learning perspective
Peter Stone and Manuela Veloso · 2000
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The Grid: Blueprint for a New Computing Infrastructure
Ian Foster and Carl Kesselman · 2001
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Multi-agent teamwork in dynamic and uncertain environments
Gal A. Kaminka and Milind Tambe · 2002
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Language models are few-shot learners
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An Introduction to MultiAgent Systems
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Introduction to probability models
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Noise reduction techniques in collaborative llm environments
Lin Huang and Qiang Chen · 2023
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Decentralized context management in llm-driven multi-agent systems
Xing Li and Hao Zhang · 2023
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Optimizing context sharing in multi-agent systems using large language models
Mei Zhao and Yu Li · 2023
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Llmarena: Evaluating llms in dynamic multi-agent environments
Hong Chen and Jie Wang · 2024
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Macnet: Structured communication framework for llm-based multi-agent reasoning
Li Qian and Wei Zhou · 2024
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Methods for task allocation via agent coalition formation
Onn Shehory and Sarit Kraus
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Task allocation in mas using combinatorial auctions
Onn Shehory and Sarit Kraus
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Trustsim: Simulating human trust in multi-agent systems using llms
Dong Xie and Zhen Liu · 2024
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