PPO-PyTorch
Pytorch-PCGrad
PPO-PyTorch | Pytorch-PCGrad | |
---|---|---|
2 | 1 | |
1,493 | 265 | |
- | - | |
2.8 | 1.8 | |
5 months ago | almost 3 years ago | |
Python | Python | |
MIT License | BSD 3-clause "New" or "Revised" License |
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PPO-PyTorch
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Where does the loss function for Policy Gradient come from?
It's just very convient implementation wise, in just a few lines you can get the "loss": (from https://github.com/nikhilbarhate99/PPO-PyTorch/blob/master/PPO.py)
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A2C/PPO with continuous action space
In some methods, like the one here, the actor network has two heads, one for the mean and one for the variance. In other methods, like the one here, the network only outputs the mean, while the variance is pre-defined and is decaying throughout the training.
Pytorch-PCGrad
What are some alternatives?
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
pytorch-grad-norm - Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning adjustable weight coefficients.
l2rpn-baselines - L2RPN Baselines a repository to host baselines for l2rpn competitions.
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
pytorch-accelerated - A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/
muzero-general - MuZero
nes-torch - Minimal PyTorch Library for Natural Evolution Strategies
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
autonomous-learning-library - A PyTorch library for building deep reinforcement learning agents.
pytorch-learn-reinforcement-learning - A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.