pomdp-baselines
recurrent-ppo-truncated-bptt
| pomdp-baselines | recurrent-ppo-truncated-bptt | |
|---|---|---|
| 5 | 6 | |
| 275 | 106 | |
| - | - | |
| 4.3 | 3.2 | |
| 7 months ago | 6 days ago | |
| Python | Jupyter Notebook | |
| MIT License | MIT License |
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pomdp-baselines
- Best recurrent RL library?
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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.
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[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
recurrent-ppo-truncated-bptt
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What RL library supports custom LSTM and Transformer neural networks to use with algorithms such as PPO?
I provide baseline implementations on TransformerXL + PPO and LSTM/GRU + PPO. These are designed to be slim and easy-to-follow so that you can advance those implementations to the features and toolset that you need.
- How does a recurrent generator work in PPO?
- LSTM encoder in the policy?
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what is the best approach to POMDP environment?
Second, when training a limited view agent in a tabular environment, I expected the rppo agent to perform better than cnn-based ppo. But it didn't. I used this repository that was already implemented and saw slow learning based on this.
- LSTM with SAC not learning well on tasks like Mountain Car and Lunar Lander?
- Recurrent PPO using truncated BPTT
What are some alternatives?
tianshou - An elegant PyTorch deep reinforcement learning library.
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
snakeAI - testing MLP, DQN, PPO, SAC, policy-gradient by snake
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).
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
neroRL - Deep Reinforcement Learning Framework done with PyTorch
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)