pomdp-baselines
DeepRL-TensorFlow2
pomdp-baselines | DeepRL-TensorFlow2 | |
---|---|---|
5 | 2 | |
275 | 573 | |
- | - | |
4.3 | 0.0 | |
7 months ago | almost 2 years ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
pomdp-baselines
- Best recurrent RL library?
-
In Latest Machine Learning Research, A Group at CMU Release a Simple and Efficient Implementation of Recurrent Model-Free Reinforcement Learning (RL) for Future Work to Use as a Baseline for POMDP Algorithms
Continue reading| Check out the paper, github link, project and reference article.
-
[R] Recurrent Model-Free RL is a Strong Baseline for Many POMDPs
Code for https://arxiv.org/abs/2110.05038 found: https://github.com/twni2016/pomdp-baselines
DeepRL-TensorFlow2
-
PPO implementation in TensorFlow2
I've been searching for a clean, good, and understandable implementation of PPO for continuous action space with TF2 witch is understandable enough for me to apply my modifications, but the closest thing that I have found is this code which seems to not work properly even on a simple gym cartpole env (discussed issues in git-hub repo suggest the same problem) so I have some doubts :). I was wondering whether you could recommend an implementation that you trust and suggest :)
-
Question about using tf.stop_gradient in separate Actor-Critic networks for A2C implementation for TF2
I have been looking at this implementation of A2C. Here the author of the code uses stop_gradient only on the critic network at L90 bur not in the actor network L61 for the continuous case. However , it is used both in actor and critic networks for the discrete case. Can someone explain me why?
What are some alternatives?
tianshou - An elegant PyTorch deep reinforcement learning library.
soft-actor-critic - Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
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).
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
ydata-synthetic - Synthetic data generators for tabular and time-series data
recurrent-ppo-truncated-bptt - Baseline implementation of recurrent PPO using truncated BPTT
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...