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Multi-agent

357 articles · Page 4 of 4
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
Jul 5, 2025 · Artificial Intelligence

Building Multi-Agent Systems with Spring AI and Langgraph4j: A Hands‑On Guide

This article introduces multi‑agent architectures and the Agents Handoff pattern, then demonstrates a complete implementation using Spring Boot 3.4.2, Langgraph4j, and Spring AI, including code for a marketplace agent, a payment agent, configuration, testing, and suggestions for further improvement.

Artificial IntelligenceJavaLangGraph4j
0 likes · 10 min read
Building Multi-Agent Systems with Spring AI and Langgraph4j: A Hands‑On Guide
Su San Talks Tech
Su San Talks Tech
Jun 26, 2025 · Artificial Intelligence

Master Spring AI Alibaba 1.0: Upgrade Guide, New Features & Real‑World Code

This article walks you through what Spring AI Alibaba 1.0 offers, highlights its major updates such as the Graph multi‑agent framework and ecosystem integrations, and provides a step‑by‑step upgrade path with Maven dependency changes, code fixes, and configuration adjustments for Java developers.

AI FrameworkGraphMCP
0 likes · 20 min read
Master Spring AI Alibaba 1.0: Upgrade Guide, New Features & Real‑World Code
Tencent Technical Engineering
Tencent Technical Engineering
Jun 20, 2025 · Artificial Intelligence

Mastering AI Agents: Core Concepts, Protocols, and Golang Frameworks for Multi‑Agent Collaboration

This comprehensive article explores the evolution of AI agents, explains key protocols like MCP and A2A, compares reasoning frameworks such as CoT, ReAct, and Plan‑and‑Execute, and demonstrates how Golang frameworks Eino and tRPC‑A2A‑Go enable elegant development, orchestration, and observability of complex multi‑agent systems with practical code examples and visual diagrams.

A2AAI agentEino
0 likes · 55 min read
Mastering AI Agents: Core Concepts, Protocols, and Golang Frameworks for Multi‑Agent Collaboration
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 20, 2025 · Artificial Intelligence

How to Build High‑Availability AI Agents: Challenges, Strategies, and Real‑World Insights

This article explores the evolving concept of AI agents, debates their definitions, outlines four major deployment challenges—including prompt instability, planning balance, domain knowledge integration, and response speed—and presents practical strategies such as prompt engineering, workflow design, multi‑agent architectures, and model optimization to build reliable, high‑availability agents.

AI agentAgentic SystemsLLM
0 likes · 32 min read
How to Build High‑Availability AI Agents: Challenges, Strategies, and Real‑World Insights
Alibaba Cloud Developer
Alibaba Cloud Developer
May 26, 2025 · Artificial Intelligence

How Multi‑Agent Planning Boosts Copilot 3.0 with DeepSeek R1 GRPO Training

This article examines Copilot 3.0’s planning module, explains how DeepSeek R1’s GRPO reinforcement‑learning pipeline enables flexible multi‑agent orchestration, addresses the limitations of Copilot 2.0, and presents experimental results that show a 61% reduction in reasoning length and a 9% relative gain in accuracy.

AIMulti-agentReward Design
0 likes · 14 min read
How Multi‑Agent Planning Boosts Copilot 3.0 with DeepSeek R1 GRPO Training
Tencent Technical Engineering
Tencent Technical Engineering
May 23, 2025 · Artificial Intelligence

The Evolution, Challenges, and Future Directions of AI Agents

An in‑depth overview traces the development of AI agents from early LLM milestones to modern “class‑Agent” models, examines core components such as memory, tool use, planning and reflection, analyzes current limitations, and outlines emerging solutions like workflows, multi‑agent systems, and model‑as‑product paradigms.

AI agentFunction CallMulti-agent
0 likes · 40 min read
The Evolution, Challenges, and Future Directions of AI Agents
Alibaba Cloud Native
Alibaba Cloud Native
May 16, 2025 · Artificial Intelligence

Boost AI Reliability with MetaGPT’s Multi‑Agent Collaboration on Serverless Function AI

This guide explains how MetaGPT’s multi‑agent architecture eliminates the logical gaps of single‑agent systems, improves task stability, and can be rapidly deployed on Alibaba Cloud’s Serverless Function AI platform with step‑by‑step instructions, configuration details, and example applications.

AI DeploymentFunction AIMetaGPT
0 likes · 8 min read
Boost AI Reliability with MetaGPT’s Multi‑Agent Collaboration on Serverless Function AI
Ops Development & AI Practice
Ops Development & AI Practice
Apr 18, 2025 · Artificial Intelligence

Mastering LoopAgent: Orchestrating Multi‑Agent Workflows with ADK

This article explains how the LoopAgent component of the Agent Development Kit enables coordinated, iterative execution of multiple sub‑agents, detailing its key parameters, workflow, multi‑agent collaboration patterns, and how iterative refinement improves complex AI task outcomes.

AI OrchestrationAgent Development KitIterative refinement
0 likes · 6 min read
Mastering LoopAgent: Orchestrating Multi‑Agent Workflows with ADK
Ma Wei Says
Ma Wei Says
Apr 16, 2025 · Artificial Intelligence

How Google’s A2A Protocol Enables Seamless AI Agent Collaboration

Google’s open‑source A2A (Agent‑to‑Agent) protocol, unveiled at Google Cloud Next 2025, defines a standardized, secure, Web‑based framework that lets heterogeneous AI agents discover each other, negotiate interactions, and manage cross‑agent tasks, supporting multimodal communication, long‑running jobs, and push notifications.

A2A protocolAI agentGoogle Cloud
0 likes · 11 min read
How Google’s A2A Protocol Enables Seamless AI Agent Collaboration
Software Engineering 3.0 Era
Software Engineering 3.0 Era
Apr 11, 2025 · Artificial Intelligence

A2A vs MCP: A Comprehensive Comparison of AI Interoperability Protocols

The article provides an in‑depth comparison of Google’s Agent2Agent (A2A) protocol and Anthropic’s Model Context Protocol (MCP), examining their design philosophies, technical architectures, feature sets, ecosystem support, suitable scenarios, challenges, and potential future convergence for AI agent interoperability.

A2AAIAgent Protocol
0 likes · 15 min read
A2A vs MCP: A Comprehensive Comparison of AI Interoperability Protocols
JD Cloud Developers
JD Cloud Developers
Mar 24, 2025 · Artificial Intelligence

How Multi-Agent Reinforcement Learning Boosts Ad Computation Allocation

This article presents MaRCA, a multi‑agent reinforcement‑learning framework that allocates computation resources across the full ad‑serving chain, modeling user value, compute cost, and action rewards to maximize ad revenue while keeping system load stable under fluctuating traffic.

AIMulti-agentad optimization
0 likes · 16 min read
How Multi-Agent Reinforcement Learning Boosts Ad Computation Allocation
21CTO
21CTO
Mar 16, 2025 · Artificial Intelligence

How Google’s AI Co‑Scientist Is Accelerating Biomedical Discoveries

Google unveiled an AI co‑scientist built on Gemini 2.0 that uses multiple specialized agents to generate, evaluate, and refine research hypotheses, demonstrating promising results in drug repurposing, liver fibrosis target discovery, and antibiotic resistance, while also highlighting current limitations and community reactions.

AIGoogle AIMulti-agent
0 likes · 6 min read
How Google’s AI Co‑Scientist Is Accelerating Biomedical Discoveries
AI Product Manager Community
AI Product Manager Community
Mar 8, 2025 · Artificial Intelligence

How OWL AI Agent Outperforms OpenManus: Technical Deep Dive

The article introduces the OWL (Optimized Workforce Learning) general‑purpose AI agent, explains its six‑step architecture, benchmark performance surpassing OpenManus, and argues that its innovations represent genuine application‑level advancement rather than mere “shell‑wrapping,” while highlighting its multi‑agent collaboration framework.

AIMulti-agentautomation
0 likes · 5 min read
How OWL AI Agent Outperforms OpenManus: Technical Deep Dive
AI Algorithm Path
AI Algorithm Path
Mar 6, 2025 · Artificial Intelligence

How Manus’s General AI Agent Could Redefine Future Workflows

Manus, billed as the world’s first true general AI agent, combines multi‑agent architecture, tool integration, and superior GAIA benchmark performance to automate complex tasks, while its invitation‑only rollout and ethical concerns illustrate the tension between hype‑driven marketing and sustainable AI adoption.

AI agentGAIA benchmarkManus
0 likes · 6 min read
How Manus’s General AI Agent Could Redefine Future Workflows
Fun with Large Models
Fun with Large Models
Mar 2, 2025 · Artificial Intelligence

Why 2025 Is the Year of AI Agents: Definitions, Types, and Real‑World Examples

The article explains what AI Agents are, how they differ from single large‑model systems, outlines four agent architectures—Reflection, Tool Use, Planning, and Multi‑Agent—and cites concrete examples from Grammarly, VS Code plugins, Image Describer X, ChatDev, as well as initiatives by Tencent and Google, highlighting the 2025 AI Agent boom.

ChatDevMulti-agentplanning
0 likes · 9 min read
Why 2025 Is the Year of AI Agents: Definitions, Types, and Real‑World Examples
JD Tech Talk
JD Tech Talk
Feb 20, 2025 · Artificial Intelligence

Multi‑Agent Architecture for an E‑Commerce Business Assistant: Design, Planning, Evaluation, and Sample Generation

The document describes the evolution, design principles, key technologies, online inference workflow, evaluation methods, and sample‑generation techniques of a large‑language‑model‑based multi‑agent system that powers a 24/7 e‑commerce merchant assistant, highlighting its benefits, challenges, and future work.

AI planningLLMMulti-agent
0 likes · 21 min read
Multi‑Agent Architecture for an E‑Commerce Business Assistant: Design, Planning, Evaluation, and Sample Generation
JD Cloud Developers
JD Cloud Developers
Feb 20, 2025 · Artificial Intelligence

How Multi‑Agent ReAct Architecture Boosts E‑Commerce AI Assistants

This article explains the evolution of multi‑agent systems for e‑commerce assistants, detailing the ReAct‑based planning framework, hierarchical master‑sub agent collaboration, evaluation methods, and sample‑generation techniques that together improve accuracy, efficiency, and scalability of AI‑driven merchant services.

AI planningAgent ArchitectureLLM
0 likes · 23 min read
How Multi‑Agent ReAct Architecture Boosts E‑Commerce AI Assistants
JD Retail Technology
JD Retail Technology
Feb 10, 2025 · Artificial Intelligence

JD Merchant Intelligent Assistant: Multi‑Agent Architecture and Technical Exploration

The JD Merchant Intelligent Assistant employs a large‑language‑model‑driven multi‑agent architecture with dynamic ReAct planning, enabling merchants to query and execute store operations in under a second with over 90 % decision accuracy, while reducing inference cost, hallucinations, and engineering effort across diverse e‑commerce tasks.

AILLMMulti-agent
0 likes · 25 min read
JD Merchant Intelligent Assistant: Multi‑Agent Architecture and Technical Exploration
Infra Learning Club
Infra Learning Club
Feb 8, 2025 · Artificial Intelligence

Multi-Agent LLMs Explained: Benefits, Workflows, and Leading Frameworks

The article surveys the rise of multi‑agent LLM systems, detailing how specialized agents collaborate on tasks such as travel planning, outlining their workflow, comparing them with single‑agent models, listing prominent frameworks, and discussing current challenges and research citations.

AIAutoGenFrameworks
0 likes · 13 min read
Multi-Agent LLMs Explained: Benefits, Workflows, and Leading Frameworks
AI Large Model Application Practice
AI Large Model Application Practice
Dec 23, 2024 · Artificial Intelligence

Master LlamaIndex Workflows: Build Multi‑Agent RAG Applications Step‑by‑Step

This article introduces LlamaIndex Workflows, explains its event‑driven design, walks through a multi‑agent demo that combines weather search and email sending, provides complete Python code for defining events, steps, and the orchestrator, and compares its strengths and limitations against similar frameworks.

AIMulti-agentPython
0 likes · 13 min read
Master LlamaIndex Workflows: Build Multi‑Agent RAG Applications Step‑by‑Step
AI Large Model Application Practice
AI Large Model Application Practice
Dec 12, 2024 · Artificial Intelligence

Mastering AutoGen: Build Multi‑Agent LLM Applications in Minutes

AutoGen, Microsoft’s advanced multi‑agent framework, lets developers quickly assemble collaborative LLM agents—supporting chat, tool use, and hierarchical group chats—through concise Python code, with examples ranging from simple two‑agent dialogues to complex three‑agent reporting pipelines, while outlining its strengths, limitations, and upcoming v0.4 enhancements.

AIAutoGenLLM
0 likes · 9 min read
Mastering AutoGen: Build Multi‑Agent LLM Applications in Minutes
Alimama Tech
Alimama Tech
Dec 11, 2024 · Artificial Intelligence

Engineering Architecture of Alibaba's AI Digital Employee "AI XiaoWan"

Alibaba’s AI digital employee “AI XiaoWan” uses a native multi‑agent architecture where a Controller Agent interprets intent, plans tasks, and orchestrates execution while an Executable Agent performs domain‑specific operations, communicating via a standardized Agent Communication Protocol, leveraging a centralized Tool Center, a retrieval‑augmented knowledge base, and a data‑flywheel feedback loop to continuously improve and evolve toward memory‑based reasoning and self‑learning.

AIMulti-agentRAG
0 likes · 14 min read
Engineering Architecture of Alibaba's AI Digital Employee "AI XiaoWan"
AI Large Model Application Practice
AI Large Model Application Practice
Dec 2, 2024 · Artificial Intelligence

Master CrewAI: Build Multi‑Agent Systems Quickly with Flows and a Full Demo

This article introduces CrewAI, a high‑level Python framework for constructing multi‑agent systems, explains its core concepts such as Crew, Agent, Tool, Task and Process, walks through a complete demo with code, evaluates its strengths and limitations, and showcases the new Flows feature for more flexible workflow orchestration.

AI FrameworkCrewAIFlows
0 likes · 15 min read
Master CrewAI: Build Multi‑Agent Systems Quickly with Flows and a Full Demo
Huolala Tech
Huolala Tech
Sep 26, 2024 · Artificial Intelligence

How LLM-Powered AI Assistants Transform Logistics Operations

This article details Huolala's exploration of large‑language‑model (LLM) based AI assistants across multiple business scenarios, describing their architecture, implementation challenges, prompt engineering techniques, and the progressive stages from professional assistants to multi‑agent systems that drive efficiency and innovation in logistics.

AI assistantLLMMulti-agent
0 likes · 12 min read
How LLM-Powered AI Assistants Transform Logistics Operations
21CTO
21CTO
Sep 5, 2024 · Artificial Intelligence

How Microsoft’s AutoGen Studio Simplifies Multi‑Agent AI Development

Microsoft Research’s AutoGen Studio offers a low‑code web and Python interface built on the open‑source AutoGen framework, enabling developers to quickly prototype, enhance, and combine AI agents into complex workflows while providing drag‑and‑drop design, debugging tools, and Azure integration for secure, scalable multi‑agent applications.

AI AgentsAutoGenMicrosoft
0 likes · 7 min read
How Microsoft’s AutoGen Studio Simplifies Multi‑Agent AI Development
DataFunSummit
DataFunSummit
Aug 25, 2024 · Artificial Intelligence

Applying Large AI Models to Financial Data Governance and Innovative Use Cases

This article presents a comprehensive technical overview of how large AI models are reshaping financial data production, governance, multimodal document understanding, lakehouse storage, private‑domain model deployment, data‑centric engineering methods, and multi‑agent intelligent advisory within the finance sector.

AIMulti-agentMultimodal
0 likes · 21 min read
Applying Large AI Models to Financial Data Governance and Innovative Use Cases
AI Large Model Application Practice
AI Large Model Application Practice
Aug 22, 2024 · Artificial Intelligence

Building a Multi‑Agent AI Research Assistant with LangGraph and GPT‑Researcher

This article explains how to construct a multi‑agent AI research assistant using LangGraph and the open‑source GPT‑Researcher project, detailing the system architecture, agent roles, state design, workflow creation, parallel sub‑processes, and code examples for autonomous online research and report generation.

AIGPT-ResearcherLangGraph
0 likes · 13 min read
Building a Multi‑Agent AI Research Assistant with LangGraph and GPT‑Researcher
Baidu Geek Talk
Baidu Geek Talk
Jul 15, 2024 · Industry Insights

How AI Is Revolutionizing Physical Network Fault Localization

This article explains how Baidu Cloud evolved from manual and integrated network fault detection to AI-driven localization using large language models, detailing structured prompting, multi‑agent workflows, and real‑world comparisons that demonstrate improved accuracy and faster mitigation.

AIInfrastructureMulti-agent
0 likes · 14 min read
How AI Is Revolutionizing Physical Network Fault Localization
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Jul 10, 2024 · Artificial Intelligence

How AI Transforms Physical Network Fault Localization: From Manual to LLM‑Powered Precision

This article explains how Baidu Cloud evolved its physical network fault‑location workflow—from manual analysis and integrated multi‑signal algorithms to AI‑driven reasoning with large language models—highlighting structured prompting, multi‑agent collaboration, and measurable improvements in accuracy and automation.

AIMulti-agentautomation
0 likes · 15 min read
How AI Transforms Physical Network Fault Localization: From Manual to LLM‑Powered Precision
JD Cloud Developers
JD Cloud Developers
May 29, 2024 · Artificial Intelligence

How Multi‑Agent AI Is Revolutionizing E‑Commerce Decision Making

This article explores JD Retail's AI‑driven multi‑agent system that mimics real‑world merchant decision processes, detailing the ReAct paradigm, agent roles, workflow, training methods, monitoring, and future directions for building intelligent e‑commerce assistants.

AIAgent ArchitectureFine-tuning
0 likes · 21 min read
How Multi‑Agent AI Is Revolutionizing E‑Commerce Decision Making
JD Tech
JD Tech
May 22, 2024 · Artificial Intelligence

AI Multi‑Agent System for E‑commerce Merchant Assistance: Design, ReAct Architecture, and Implementation

The article describes JD Retail's AI‑driven multi‑agent platform that models real‑world merchant decision‑making with ReAct‑based LLM agents, detailing the system architecture, agent roles, reasoning loops, workflow examples, training pipelines, monitoring, and future directions for e‑commerce support.

AIDecision SupportLLM
0 likes · 21 min read
AI Multi‑Agent System for E‑commerce Merchant Assistance: Design, ReAct Architecture, and Implementation
JD Retail Technology
JD Retail Technology
May 22, 2024 · Artificial Intelligence

AI Multi‑Agent System for E‑commerce: Design, Implementation, and Operational Insights

This article presents a comprehensive overview of JD Retail's AI‑driven multi‑agent architecture for e‑commerce assistance, detailing how real‑world merchant decision processes are modeled with ReAct‑based LLM agents, the hierarchical workflow, training pipelines, monitoring mechanisms, and future directions for scalable intelligent commerce support.

AIAgent ArchitectureKnowledge Retrieval
0 likes · 20 min read
AI Multi‑Agent System for E‑commerce: Design, Implementation, and Operational Insights
Efficient Ops
Efficient Ops
May 14, 2024 · Artificial Intelligence

How Large‑Model Agents Are Revolutionizing AIOps and Modern Operations

This article explores why large‑model Agent technology is essential for AIOps, explains single‑ and multi‑Agent architectures, memory and tool integration, and demonstrates practical applications such as anomaly detection, fault diagnosis, automated remediation, ChatOps, and future directions for intelligent, autonomous operations.

AI AgentsAIOpsLLM
0 likes · 14 min read
How Large‑Model Agents Are Revolutionizing AIOps and Modern Operations
AntTech
AntTech
Apr 19, 2024 · Artificial Intelligence

AgentUniverse: An Enterprise‑Grade Multi‑Agent Framework for Complex Financial Analysis

The article introduces AgentUniverse, a large‑model multi‑agent framework that orchestrates specialized agents through a PEER collaboration pattern to overcome LLM limitations in complex financial tasks, demonstrates its architecture, workflow, experimental superiority on benchmarks, and provides open‑source installation details.

AIAgent FrameworkFinancial Analysis
0 likes · 10 min read
AgentUniverse: An Enterprise‑Grade Multi‑Agent Framework for Complex Financial Analysis
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Apr 12, 2024 · Artificial Intelligence

Typical Business and Technical Architectures for Large Language Model Applications

This article reviews the common business and technical architectures used in large language model (LLM) applications, explains AI Embedded, AI Copilot, and AI Agent modes—including single‑ and multi‑agent systems—and offers guidance on selecting appropriate technology stacks such as prompt‑only, function‑calling agents, RAG, and fine‑tuning.

AI agentFine-tuningLLM
0 likes · 9 min read
Typical Business and Technical Architectures for Large Language Model Applications
DataFunTalk
DataFunTalk
Apr 8, 2024 · Artificial Intelligence

LLM‑Based Agents: Architecture, Key Challenges, and Future Directions

This article surveys the emerging field of large‑language‑model (LLM) based agents, detailing their modular architecture—including profiling, memory, planning, and action components—while discussing critical challenges such as role‑playing, memory design, reasoning, multi‑agent collaboration, and outlining promising research directions and practical case studies.

AI agentAgent ArchitectureLLM
0 likes · 11 min read
LLM‑Based Agents: Architecture, Key Challenges, and Future Directions
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 7, 2024 · Artificial Intelligence

Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab

This tutorial walks through installing LangChain, LangGraph and related packages in Google Colab, configuring environment variables, defining search and Twitter‑writer tools, constructing a StateGraph workflow with supervisor logic, and executing a multi‑agent LLM pipeline using LangChain’s new multi‑agent capabilities.

AIGoogle ColabLLM
0 likes · 11 min read
Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Dec 6, 2023 · Artificial Intelligence

Multi-Agent Research Overview, Open-Source Implementations, and Design Considerations

This article reviews the background of multi‑agent systems, compares major open‑source frameworks such as AutoGen, MetaGPT, AgentVerse, and XAgent, discusses design principles, collaboration strategies, and offers conclusions on LLM‑driven versus SOP‑driven approaches for building multi‑agent applications.

AIAgent FrameworkAutoGen
0 likes · 15 min read
Multi-Agent Research Overview, Open-Source Implementations, and Design Considerations
AI Large Model Application Practice
AI Large Model Application Practice
Oct 4, 2023 · Artificial Intelligence

Controlling LLM‑Based AI Agents with the Open‑Source ‘Agents’ Framework

This article introduces the experimental open‑source project ‘Agents’, explains common challenges of LLM‑based AI agents, compares it with tools like AutoGPT, LangChain and MetaGPT, and demonstrates how its configuration‑driven SOP approach enables more controllable, multi‑agent interactions and easier deployment.

ConfigurationLLMMulti-agent
0 likes · 14 min read
Controlling LLM‑Based AI Agents with the Open‑Source ‘Agents’ Framework
Alimama Tech
Alimama Tech
Oct 20, 2021 · Artificial Intelligence

Highlights of Recent Alibaba Advertising Research Papers Presented at WSDM 2022

At WSDM 2022, Alibaba’s advertising team presented four papers introducing a meta‑learning multi‑task multi‑scenario model for advertiser forecasting, a low‑cost Feature Co‑Action Network that boosts CTR prediction, an Adaptive Unified Allocation Framework that improves guaranteed display fulfillment and CTR, and a cooperative‑competitive multi‑agent auto‑bidding system that enhances both advertiser welfare and platform profit.

Meta-LearningMulti-agentOnline Advertising
0 likes · 11 min read
Highlights of Recent Alibaba Advertising Research Papers Presented at WSDM 2022
Tencent Tech
Tencent Tech
Dec 31, 2020 · Artificial Intelligence

How Tencent’s WeKick AI Dominated the Google Football Kaggle Competition

Tencent AI Lab’s WeKick AI clinched the inaugural Google Football Kaggle championship with a score of 1785.8, outpacing over 1,100 research teams by leveraging a migrated full‑stack architecture, custom reinforcement‑learning frameworks, GAIL imitation learning, and a multi‑style League training pipeline that together showcase the power and generality of deep reinforcement learning for complex multi‑agent tasks.

AIGAILGoogle Football
0 likes · 8 min read
How Tencent’s WeKick AI Dominated the Google Football Kaggle Competition