Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control VS stable-baselines3

Compare Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs stable-baselines3 and see what are their differences.

Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control

Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments (by SimonRennotte)
reinforcement-learning Pytorch pytorch-implementation gpytorch gaussian-processes model-predictive-control model-based-reinforcement-learning Paper control-animation uncertainty
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stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms. (by DLR-RM)
reinforcement-learning reinforcement-learning-algorithms Machine Learning Gym openai baselines Toolbox stable-baselines Python Pytorch Robotics Sde gsde sb3
Source Code
stable-baselines3.readthedocs.io
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Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control stable-baselines3
2 46
114 7,953
- 3.1%
4.5 8.2
12 months ago 8 days ago
Python Python
MIT License MIT License
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Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control

Posts with mentions or reviews of Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control. We have used some of these posts to build our list of alternatives and similar projects.

stable-baselines3

Posts with mentions or reviews of stable-baselines3. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-09.

What are some alternatives?

When comparing Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control and stable-baselines3 you can also consider the following projects:

Machine-Learning-Collection - A resource for learning about Machine learning & Deep Learning

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.

ProSelfLC-AT - noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

ALAE - [CVPR2020] Adversarial Latent Autoencoders

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

tianshou - An elegant PyTorch deep reinforcement learning library.

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥

Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs Machine-Learning-Collection stable-baselines3 vs Ray Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs ProSelfLC-AT stable-baselines3 vs stable-baselines Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs Robo-Semantic-Segmentation stable-baselines3 vs Pytorch Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs ALAE stable-baselines3 vs cleanrl Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs d2l-en stable-baselines3 vs tianshou stable-baselines3 vs Super-mario-bros-PPO-pytorch stable-baselines3 vs ElegantRL