rlqp
machin
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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 ‘RLQP’ To Accelerate Quadratic Optimization With Deep Reinforcement Learning (RL)
machin
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Best PyTorch RL library for doing research
Machin is really nice, it is very easy to use and to try different things, although it’s developed by one person and maybe not appropriately tested yet.
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Is there a consensus about RL frameworks?
I found this repo very helpful to get started: https://github.com/iffiX/machin
What are some alternatives?
rlalgorithms-tf2 - Packaged deep reinforcement learning algorithms in tensorflow 2.x
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Apache Impala - Apache Impala
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
tianshou - An elegant PyTorch deep reinforcement learning library.
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
dcss-ai-wrapper - An API for Dungeon Crawl Stone Soup for Artificial Intelligence research.
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Deep-Reinforcement-Learning-Algorithms-with-PyTorch - PyTorch implementations of deep reinforcement learning algorithms and environments
bagua - Bagua Speeds up PyTorch