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Deep-reinforcement-learning-with-pytorch
sweetice/Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
★4.7kstars
Python
MIT
Updated: Today
📋 Project at a Glance
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What's this?A , built with Python open-source project in the Learning & Resources category, core strengths: a2c/a3c
Who made it?Maintained by sweetice team, 4.7K⭐ on GitHub, #451 out of 3640 in Learning & Resources
Why does it exist?As the Learning & Resources landscape evolved, the sweetice team identified the need for better a2c solutions. Deep-reinforcement-learning-with-pytorch was created to simplify a3c workflows.
What can it do?Key use cases: actor-critic, actor-critic-algorithm, algorithm
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/sweetice/Deep-reinforcement-learning-with-pytorch
🔗 github.com/sweetice/Deep-reinforcement-learning-with-pytorch
Topics
a2ca3cactor-criticactor-critic-algorithmalgorithmalphagodeep-learningdeep-reinforcement-learningdqnpolicy-gradientppopytorchreinforceresnetsacsarsatd3trpo