reinforcement-learning

Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.

reinforcement-learningopenai-gymdeep-learningmulti-agent-systems

pluginagentmarketplace

21

stable-baselines3

Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation.

pythonmachine-learningreinforcement-learningopenai-gym

K-Dense-AI

3,233360