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aceleración en investigación

  • RxAgent-Zoo uses reactive programming with RxPY to streamline development and experimentation of modular reinforcement learning agents.
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    What is RxAgent-Zoo?
    At its core, RxAgent-Zoo is a reactive RL framework that treats data events from environments, replay buffers, and training loops as observable streams. Users can chain operators to preprocess observations, update networks, and log metrics asynchronously. The library offers parallel environment support, configurable schedulers, and integration with popular Gym and Atari benchmarks. A plug-and-play API allows seamless swapping of agent components, facilitating reproducible research, rapid experimentation, and scalable training workflows.
    RxAgent-Zoo Core Features
    • Reactive RL pipelines with RxPY
    • Pre-implemented agents: DQN, PPO, A2C, DDPG
    • Parallel environment execution
    • Asynchronous data stream management
    • Built-in logging and monitoring
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