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PPO 방법

  • Open-source Python framework implementing multi-agent reinforcement learning algorithms for cooperative and competitive environments.
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    What is MultiAgent-ReinforcementLearning?
    This repository provides a complete suite of multi-agent reinforcement learning algorithms—including MADDPG, DDPG, PPO, and more—integrated with standard benchmarks like the Multi-Agent Particle Environment and OpenAI Gym. It features customizable environment wrappers, configurable training scripts, real-time logging, and performance evaluation metrics. Users can easily extend algorithms, adapt to custom tasks, and compare policies across cooperative and adversarial settings with minimal setup.
    MultiAgent-ReinforcementLearning Core Features
    • Implementations of MADDPG, DDPG, PPO
    • Environment wrappers for Multi-Agent Particle and Gym
    • Configurable training and evaluation scripts
    • Real-time logging with TensorBoard
    • Modular codebase for extension
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