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AI実験の設定

  • A Keras-based implementation of Multi-Agent Deep Deterministic Policy Gradient for cooperative and competitive multi-agent RL.
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    What is MADDPG-Keras?
    MADDPG-Keras delivers a complete framework for multi-agent reinforcement learning research by implementing the MADDPG algorithm in Keras. It supports continuous action spaces, multiple agents, and standard OpenAI Gym environments. Researchers and developers can configure neural network architectures, training hyperparameters, and reward functions, then launch experiments with built-in logging and model checkpointing to accelerate multi-agent policy learning and benchmarking.
    MADDPG-Keras Core Features
    • Keras & TensorFlow implementation of MADDPG
    • Support for continuous action spaces
    • Configurable multi-agent Gym environments
    • Logging, tensorboard integration, and checkpointing
    • Customizable neural network architectures
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