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輕量級設計

  • A Go library to create and simulate concurrent AI agents with sensors, actuators, and messaging for complex multi-agent environments.
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    What is multiagent-golang?
    multiagent-golang provides a structured approach to building multi-agent systems in Go. It introduces an Agent abstraction where each agent can be equipped with various sensors to perceive its environment and actuators to take actions. Agents run concurrently using Go routines and communicate through dedicated messaging channels. The framework also includes an environment simulation layer to handle events, manage the agent lifecycle, and track state changes. Developers can easily extend or customize agent behaviors, configure simulation parameters, and integrate additional modules for logging or analytics. It streamlines the creation of scalable, concurrent simulations for research and prototyping.
    multiagent-golang Core Features
    • Agent abstraction with sensors and actuators
    • Concurrent agent execution using Go routines
    • Inter-agent messaging channels
    • Environment simulation and event handling
    • Agent lifecycle and behavior configuration
    • Lightweight and modular design
  • A Java-based multi-agent communication demo using JADE, showcasing two-way interaction, message parsing, and agent coordination.
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    What is Two-Way Agent Communication using JADE?
    This repository provides a hands-on demonstration of two-way communication between agents built on the JADE framework. It includes example Java classes showing agent setup, FIPA-ACL compliant message creation, and asynchronous behavior handling. Developers can study Agent A sending a REQUEST, Agent B processing the request, and returning an INFORM message. The code illustrates registering agents with the Directory Facilitator, using cyclic and one-shot behaviors, applying message templates to filter messages, and logging conversation sequences. It’s an ideal starting point for prototyping multi-agent exchanges, custom protocols, or integrating JADE agents into larger distributed AI systems.
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