Note
softlearning
Note | softlearning | |
---|---|---|
48 | 4 | |
35 | 1,159 | |
- | 1.8% | |
9.9 | 0.0 | |
4 days ago | 5 months ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Note
- Easily implement parallel training.
- This project allows you to easily implement parallel training with the multiprocessing module.
-
Train neural networks in parallel using Python's multiprocessing module.
https://github.com/NoteDancing/Note This project allows you to train neural network in parallel using Python's multiprocessing module.
- A system for deep learning and reinforcement learning.
- A system for deep learning and reinforcement learning. (r/MachineLearning)
- [P] A system for deep learning and reinforcement learning.
softlearning
-
Problem with Truncated Quantile Critics (TQC) and n-step learning algorithm.
# see https://github.com/rail-berkeley/softlearning/issues/60
-
Infinite Horizon problem with SAC and custom environment
Found relevant code at https://github.com/rail-berkeley/softlearning + all code implementations here
-
SAC: Enforcing Action Bounds formula derivation
Code for https://arxiv.org/abs/1812.05905 found: https://github.com/rail-berkeley/softlearning
-
DDPG not solving MountainCarContinuous
You may read - issue with SAC (https://github.com/rail-berkeley/softlearning/issues/76 ), solution: use large OU noise or use other type of exploration like gSDE
What are some alternatives?
deep-RL-trading - playing idealized trading games with deep reinforcement learning
deep-significance - Enabling easy statistical significance testing for deep neural networks.
tmrl - Reinforcement Learning for real-time applications - host of the TrackMania Roborace League
quickai - QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
muzero-general - MuZero
LiDAR-Guide - LiDAR Guide
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
trax - Trax — Deep Learning with Clear Code and Speed
neptune-contrib - This library is a location of the LegacyLogger for PyTorch Lightning.
awesome-deep-trading - List of awesome resources for machine learning-based algorithmic trading