skrl
dmc2gymnasium
| skrl | dmc2gymnasium | |
|---|---|---|
| 7 | 1 | |
| 410 | 4 | |
| - | - | |
| 8.7 | 3.4 | |
| 6 days ago | about 1 month ago | |
| Python | Python | |
| MIT License | MIT License |
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skrl
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Isaac Gym with Off-policy Algorithms
skrl will allow you to easily configure and use off-policy algorithms such as DDPG, TD3 and SAC in Isaac Gym, Omniverse Isaac Gym and Isaac Orbit, but I think there will not be significant gains compared to on-policy algorithms.
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Choosing a framework in 2023
Check its comprehensive documentation at https://skrl.readthedocs.io
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Best recurrent RL library?
Also, skrl. It supports RNN, LSTM, GRU, and other variants for A2C, DDPG, PPO, SAC, TD3, and TRPO agents. See the models basic usage and examples
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What is the limit on parallel environments?
In this case, I encourage you to try the skrl RL library that fully supports all of them, among others.
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What's the best "Non-Black Box" framework for SOTA algorithms?
I encourage you to try skrl (https://skrl.readthedocs.io).
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I have a PPO implementation but I am pretty sure it wrong. I need this correct because I would like to add LSTM layer over this. Could someone have a look?
I encourage you to take a look at the skrl library...
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Can we use RNN in RL?
This is the list of examples (to be included in the documentation) that includes RNN: (ddpg_gym_pendulumnovel_gru.py, ddpg_gym_pendulumnovel_lstm.py, ddpg_gym_pendulumnovel_rnn.py, etc.)... and here are some RNN benchmarking results (to be updated for the release)
dmc2gymnasium
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DM Control Suite vs. Original Environments
I'm actually working on a DMC to gymnasium wrapper right now that you might find useful https://github.com/imgeorgiev/dmc2gymnasium
What are some alternatives?
IsaacGymEnvs - Isaac Gym Reinforcement Learning Environments
gym-simplegrid - Simple Gridworld Gymnasium Environment
awesome-isaac-gym - A curated list of awesome NVIDIA Issac Gym frameworks, papers, software, and resources
Gym-Trading-Env - A simple, easy, customizable Gymnasium environment for trading.
pfrl - PFRL: a PyTorch-based deep reinforcement learning library
football - Check out the new game server:
OmniIsaacGymEnvs - Reinforcement Learning Environments for Omniverse Isaac Gym
pysc2 - StarCraft II Learning Environment
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
policy-adaptation-during-deployment - Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
envpool - C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.