Multi-Agent Programming Framework

A Multi-Agent Programming Framework is a AI agent software framework that enables the development and orchestration of multi-agent systems.

• AKA: Multi-Agent Framework.
• Context:
  • It can (typically) enable agent communication through interaction protocols.
  • It can (typically) support agent collaboration via workflow orchestration.
  • It can (typically) manage agent roles and agent behaviors.
  • It can (typically) provide tool integration for external interactions.
  • ...
  • It can (often) implement memory management for agent state.
  • It can (often) handle error recovery during execution.
  • It can (often) support human oversight via interaction interfaces.
  • It can (often) enable workflow customization through configuration options.
  • ...
  • It can have Architecture Types including centralized networks, decentralized networks, and hierarchical networks.
  • It can provide Development Tools for agent design and deployment.
  • It can implement Security Measures for system protection.
  • It can maintain Performance Metrics for system evaluation.
  • ...
• Examples:
  • Modern Multi-Agent Frameworks, such as:
    • AutoGen Framework for conversation-based orchestration
    • CrewAI Framework for role-playing workflows
    • LangGraph Framework for graph-based execution
    • MetaGPT Framework for software company simulation
    • ...
  • Traditional Multi-Agent Frameworks, such as:
    • JADE Framework for FIPA-compliant systems
    • INGENIAS Framework for model-driven development
    • AgentSpeak Framework for BDI architectures
    • SARL Framework for general-purpose agents
    • ...
  • ...
• Counter-Examples:
  • Single-Agent Frameworks, which lack multi-agent coordination.
  • Monolithic Frameworks, which do not support agent distribution.
  • Static Frameworks, which cannot handle dynamic interactions.
• See: Software Framework, Multi-Agent System, Agent Architecture, Distributed System, Collaborative AI, System Orchestration.

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