f-IRL
ElegantRL
| f-IRL | ElegantRL | |
|---|---|---|
| 2 | 6 | |
| 35 | 3,459 | |
| - | 2.0% | |
| 1.8 | 7.1 | |
| 10 months ago | 2 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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f-IRL
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Can you use the reward learned in generative adversarial imitation learning in order to train from scratch?
Code for https://arxiv.org/abs/2011.04709 found: https://github.com/twni2016/f-IRL
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How to pretrain a model on expert data?
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
ElegantRL
- Does “massively parallel simulation” help advance Reinforcement Learning?
- ElegantRL: Cloud-Native Deep Reinforcement Learning
- ElegantRL: A Lightweight and Stable Deep Reinforcement Learning Library
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[R] ElegantRL: A Lightweight and Stable Deep Reinforcement Learning Library
The ElegantRL library is featured with “elegant” in the following aspects:
- Lightweight, Efficient and Stable DRL Library
- Lightweight, Efficient and Stable DRL Implementation Using PyTorch
What are some alternatives?
Meta-SAC - Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
falken - Falken provides developers with a service that allows them to train AI that can play their games
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
eirli - An Empirical Investigation of Representation Learning for Imitation (EIRLI), NeurIPS'21
tianshou - An elegant PyTorch deep reinforcement learning library.
imitation - Clean PyTorch implementations of imitation and reward learning algorithms
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
Deep-Reinforcement-Learning-Algorithms - 32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
pytorch-ddpg - Deep deterministic policy gradient (DDPG) in PyTorch 🚀
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...