rlqp
ElegantRL
| rlqp | ElegantRL | |
|---|---|---|
| 4 | 6 | |
| 79 | 3,501 | |
| - | 1.7% | |
| 0.0 | 7.1 | |
| over 2 years ago | 10 days ago | |
| Python | ||
| - | GNU General Public License v3.0 or later |
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rlqp
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[R] Accelerating Quadratic Optimization Up to 3x With Reinforcement Learning
Code for https://arxiv.org/abs/2107.10847 found: https://github.com/berkeleyautomation/rlqp
- AI Research Team From Princeton, Berkeley and ETH Zurich Introduce âRLQPâ To Accelerate Quadratic Optimization With Deep Reinforcement Learning (RL)
ElegantRL
- Does âmassively parallel simulationâ 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 âelegantâ in the following aspects:
- Lightweight, Efficient and Stable DRL Library
- Lightweight, Efficient and Stable DRL Implementation Using PyTorch
What are some alternatives?
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
rlalgorithms-tf2 - Packaged deep reinforcement learning algorithms in tensorflow 2.x
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.
tianshou - An elegant PyTorch deep reinforcement learning library.
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 đ
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 - Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star. [Moved to: https://github.com/AI4Finance-Foundation/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020]
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