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comunicaciones asincrónicas

  • A Java-based framework for designing, deploying, and managing autonomous multi-agent systems with communication, coordination, and dynamic behavior modeling.
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    What is Agent-Oriented Architecture?
    Agent-Oriented Architecture (AOA) is a robust framework that equips developers with tools to build and maintain intelligent multi-agent systems. Agents encapsulate state, behaviors, and interaction patterns, communicating via an asynchronous message bus. AOA includes modules for agent registration, discovery, and matchmaking, enabling dynamic service composition. Behavior modeling supports finite-state machines, goal-driven planning, and event-driven triggers. The framework handles agent lifecycle events like creation, suspension, migration, and termination. Built-in monitoring and logging facilitate performance tuning and debugging. AOA’s pluggable transport layer supports TCP, HTTP, and custom protocols, making it adaptable for on-premise, cloud, or edge deployments. Integration with popular libraries ensures seamless data processing and AI model integration.
    Agent-Oriented Architecture Core Features
    • Agent lifecycle management (creation, suspension, migration, termination)
    • Inter-agent asynchronous messaging bus
    • Service registration and discovery
    • Behavior modeling (FSMs, goal-driven planning, event-driven triggers)
    • Pluggable transport layer (TCP, HTTP, custom protocols)
    • Built-in monitoring and logging
    • Extensible plugin architecture
  • AgentVerse is a Python framework enabling developers to build, orchestrate, and simulate collaborative AI agents for diverse tasks.
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    What is AgentVerse?
    AgentVerse is designed to facilitate the creation of multi-agent architectures by offering a set of reusable modules and abstractions. Users can define unique agent classes with custom decision-making logic, establish communication channels for message passing, and simulate environmental conditions. The platform supports synchronous and asynchronous interactions among agents, enabling complex workflows such as negotiation, task delegation, and cooperative problem-solving. With integrated logging and monitoring, developers can trace agent actions and evaluate performance metrics. AgentVerse also includes templates for common use cases like autonomous exploration, trading simulations, and collaborative content generation. Its pluggable design allows seamless integration of external machine learning models, such as language models or reinforcement learning algorithms, providing flexibility for various AI-driven applications.
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