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atribuição dinâmica de tarefas

  • A Java-based implementation of the Contract Net Protocol enabling autonomous agents to dynamically negotiate and allocate tasks in multi-agent systems.
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    What is Contract Net Protocol?
    The Contract Net Protocol repository provides a full Java implementation of the FIPA Contract Net interaction protocol. Developers can create manager and contractor agents that exchange CFP (Call For Proposal), proposals, acceptances, and rejections over agent communication channels. The code includes core modules for broadcasting tasks, collecting bids, evaluating proposals based on customizable criteria, awarding contracts, and monitoring execution status. It can be integrated into larger multi-agent frameworks or used as a standalone library for research simulations, industrial scheduling, or robotic coordination.
    Contract Net Protocol Core Features
    • Call For Proposal (CFP) broadcasting
    • Bid submission and collection
    • Proposal evaluation based on custom criteria
    • Dynamic task assignment and contract award
    • Agent communication via FIPA ACL messages
  • A meta agent framework coordinating multiple specialized AI agents to collaboratively solve complex tasks across domains.
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    What is Meta-Agent-with-More-Agents?
    Meta-Agent-with-More-Agents is an extensible open-source framework that implements a meta agent architecture allowing multiple specialized sub-agents to collaborate on complex tasks. It leverages LangChain for agent orchestration and OpenAI APIs for natural language processing. Developers can define custom agents for tasks like data extraction, sentiment analysis, decision-making, or content generation. The meta agent coordinates task decomposition, dispatches objectives to appropriate agents, gathers their outputs, and iteratively refines results via feedback loops. Its modular design supports parallel processing, logging, and error handling. Ideal for automating multi-step workflows, research pipelines, and dynamic decision support systems, it simplifies building robust distributed AI systems by abstracting inter-agent communication and lifecycle management.
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