Multi-Agent Development Framework

A Multi-Agent Development 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.
- ...
Example(s):
- Modern Multi-Agent Frameworks, such as:
  - LLM Based Frameworks for language model orchestration:
    - AutoGen Framework for conversation orchestration.
    - CrewAI Framework for role based workflow.
    - LangGraph Framework for graph based execution.
    - MetaGPT Framework for software development simulation.
  - Agent Composition Frameworks for system architecture:
    - Microsoft Semantic Kernel for plugin orchestration.
    - Haystack Framework for pipeline composition.
    - Langchain Framework for chain orchestration.
- Traditional Multi-Agent Frameworks, such as:
  - FIPA Compliant Frameworks for standardized communication:
    - JADE Framework for java based agents.
    - SPADE Framework for python based agents.
    - ZEUS Framework for enterprise agents.
  - Academic Frameworks for research implementation:
    - INGENIAS Framework for model driven development.
    - AgentSpeak Framework for BDI architecture.
    - SARL Framework for general purpose agents.
- Generative Social Agent Frameworks, such as:
  - Behavioral Simulation Frameworks for human behavior:
  - Social Network Frameworks for agent community:
    - Cooperative Agent Network for group coordination.
    - Competitive Agent Framework for strategic interaction.
- Domain Specific Frameworks, such as:
  - Game AI Frameworks for virtual environments:
    - Unity ML Framework for game agents.
    - Unreal AI Framework for simulation agents.
  - Robotics Frameworks for physical agents:
    - ROS Multi-Agent Framework for robot coordination.
    - MOOS Framework for autonomous systems.
- Industrial Frameworks, such as:
  - Manufacturing Frameworks for production systems:
    - Factory Agent Framework for process automation.
    - Supply Chain Framework for logistics coordination.
  - Service Frameworks for business processes:
    - Customer Service Framework for interaction management.
    - Resource Allocation Framework for task distribution.
- Research Frameworks, such as:
  - Experimental Frameworks for agent study:
    - Cognitive Architecture Framework for mental processes.
    - Social Learning Framework for behavioral adaptation.
  - Validation Frameworks for system testing:
    - Agent Verification Framework for behavior validation.
    - Performance Benchmark Framework for system evaluation.
- Generative Social Agent Frameworks, such as:
- ...
Counter-Example(s):
- 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.