ChenglongChen/pytorch-DRL
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
This project helps researchers and practitioners in artificial intelligence experiment with and implement various Deep Reinforcement Learning (DRL) algorithms. It takes environmental observations as input and outputs optimized agent behaviors for tasks in simulated environments like CartPole or Pendulum. This is ideal for AI researchers, machine learning engineers, and students working on autonomous agents.
611 stars. No commits in the last 6 months.
Use this if you need pre-built, modular PyTorch implementations of popular DRL algorithms for both single and multi-agent scenarios to jumpstart your research or development.
Not ideal if you are looking for a high-level, production-ready framework for deploying DRL agents without needing to understand or modify the underlying algorithm implementations.
Stars
611
Forks
109
Language
Python
License
MIT
Category
Last pushed
Nov 11, 2017
Commits (30d)
0
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