Multi-Agent Systems

Three Agents Equal One GPT-4: A Collaborative Framework Based on Open Source Models

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Three Agents Equal One GPT-4: A Collaborative Framework Based on Open Source Models

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university teachers, and researchers from enterprises. The Community’s Vision is to promote communication and progress between the academic and industrial fields of natural language processing and machine learning, especially for the progress of beginners. Reprinted … Read more

War or Peace? Multi-Agent System Simulation of World War Outbreak Based on Large Language Models

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War or Peace? Multi-Agent System Simulation of World War Outbreak Based on Large Language Models

Introduction Can we avoid war at the crossroads of history? Individuals, scholars, policymakers, and organizations throughout human history have been pursuing this question. In the field of complex systems research, simulating the process of war through techniques such as wargaming and multi-agent simulation has been a long-standing topic. Especially driven by the transformative power of … Read more

Emergence of Social Norms in Multi-Agent Systems

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Emergence of Social Norms in Multi-Agent Systems

Introduction How can agents be endowed with the ability to comply with social norms and allow social norms to spontaneously emerge in AI societies? Recently, a team led by Professor Wang Zhen from Northwestern Polytechnical University and researcher Hu Shuyue from the Shanghai Artificial Intelligence Laboratory proposed the first normative framework for multi-agent systems based … Read more

Research on the Construction and Application of Teaching Intelligent Agents Based on Large Models

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Research on the Construction and Application of Teaching Intelligent Agents Based on Large Models

1. Introduction With the rapid evolution of generative artificial intelligence, multimodal large models increasingly demonstrate their advantages in multimodal content understanding and generation. Multimodal large models (hereinafter referred to as “large models”) refer to artificial intelligence models capable of processing and understanding various modalities of data inputs, including text, images, and audio-visual content. Artificial intelligence … Read more

Multi-Agent Collaboration Mechanisms: A Review of Large Language Models

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Multi-Agent Collaboration Mechanisms: A Review of Large Language Models

With the latest advancements in large language models (LLMs), agentic artificial intelligence (Agentic AI) has made significant progress in real-world applications, moving towards intelligent agents based on multiple large language models that achieve perception, learning, reasoning, and collaborative actions. These multi-agent systems (MASs) based on large language models enable a group of agents to collaborate … Read more

Swarm Lightweight Multi-Agent Orchestration Guide: Code Implementation for Scalable and Dynamic Workflows

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Swarm Lightweight Multi-Agent Orchestration Guide: Code Implementation for Scalable and Dynamic Workflows

Swarm is an innovative open-source framework designed to explore the orchestration and coordination of multi-agent systems. Developed and maintained by the OpenAI Solutions team, it provides developers with a lightweight, ergonomic, and educational environment for learning and experimenting with agent-based systems. The core design goal of Swarm is to facilitate interaction among autonomous agents (i.e., … Read more

Research and Practice on Observability of Multi-Agent Systems (OpenAI Swarm)

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Research and Practice on Observability of Multi-Agent Systems (OpenAI Swarm)

Introduction This article will introduce a research-oriented topic regarding the observability of Multi-Agent Systems. Currently, our work is primarily based on the Swarm project released by OpenAI last month, where we analyzed the source code of the Swarm project and customized modifications to achieve better observability of multi-agent systems. Today’s discussion will revolve around three … Read more

Building Multi-Agent RAG with Llama Index

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Building Multi-Agent RAG with Llama Index

Source: DeepHub IMBA This article is approximately 3000 words long and is recommended to be read in 6 minutes. This article introduces you to building multi-agent RAG using Llama index. Retrieval-Augmented Generation (RAG) has become a powerful technique for enhancing the capabilities of Large Language Models (LLMs). By retrieving relevant information from knowledge sources and … Read more

Designing Agentic AI Systems: Part Two Modularization

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Designing Agentic AI Systems: Part Two Modularization

In the first part of this series, we introduced the overall architectural pattern of Agent systems. We discussed the three logical layers of Agent systems: the Tool Layer, Action Layer, and Reasoning Layer. We also examined mechanisms such as function calls that allow large language models (LLMs) to interact with the external world through the … Read more

Overview of Best AI Agent Papers for 2024

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Overview of Best AI Agent Papers for 2024

This is an article published in the “Heroic Journey” column by the Hero. 2025 Issue No. 15 Total Issue No. 98 This article has a total of 6191 words and takes about 10 minutes to read. Contact the Hero to join the group. Stay updated with the latest insights and cutting-edge news from the global … Read more