All Projects → twni2016 → Meta-SAC

twni2016 / Meta-SAC

Licence: MIT License
Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Meta-SAC

jax-rl
JAX implementations of core Deep RL algorithms
Stars: ✭ 61 (+221.05%)
Mutual labels:  deep-reinforcement-learning, sac, mujoco, soft-actor-critic
Auto Sklearn
Automated Machine Learning with scikit-learn
Stars: ✭ 5,916 (+31036.84%)
Mutual labels:  hyperparameter-optimization, automl, meta-learning
Awesome Automl And Lightweight Models
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
Stars: ✭ 691 (+3536.84%)
Mutual labels:  hyperparameter-optimization, automl, meta-learning
proto
Proto-RL: Reinforcement Learning with Prototypical Representations
Stars: ✭ 67 (+252.63%)
Mutual labels:  sac, mujoco, soft-actor-critic
omd
JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"
Stars: ✭ 43 (+126.32%)
Mutual labels:  deep-reinforcement-learning, sac, soft-actor-critic
pomdp-baselines
Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022
Stars: ✭ 162 (+752.63%)
Mutual labels:  deep-reinforcement-learning, sac
LWDRLC
Lightweight deep RL Libraray for continuous control.
Stars: ✭ 14 (-26.32%)
Mutual labels:  deep-reinforcement-learning, sac
mindware
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Stars: ✭ 34 (+78.95%)
Mutual labels:  hyperparameter-optimization, automl
Deep RL with pytorch
A pytorch tutorial for DRL(Deep Reinforcement Learning)
Stars: ✭ 160 (+742.11%)
Mutual labels:  deep-reinforcement-learning, soft-actor-critic
Deep-Reinforcement-Learning-With-Python
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
Stars: ✭ 222 (+1068.42%)
Mutual labels:  deep-reinforcement-learning, sac
pymfe
Python Meta-Feature Extractor package.
Stars: ✭ 89 (+368.42%)
Mutual labels:  automl, meta-learning
Deep-Reinforcement-Learning-Notebooks
This Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.
Stars: ✭ 15 (-21.05%)
Mutual labels:  deep-reinforcement-learning, soft-actor-critic
Hypernets
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
Stars: ✭ 221 (+1063.16%)
Mutual labels:  hyperparameter-optimization, automl
maggy
Distribution transparent Machine Learning experiments on Apache Spark
Stars: ✭ 83 (+336.84%)
Mutual labels:  hyperparameter-optimization, automl
Rainy
☔ Deep RL agents with PyTorch☔
Stars: ✭ 39 (+105.26%)
Mutual labels:  deep-reinforcement-learning, sac
FEDOT
Automated modeling and machine learning framework FEDOT
Stars: ✭ 312 (+1542.11%)
Mutual labels:  hyperparameter-optimization, automl
ultraopt
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。
Stars: ✭ 93 (+389.47%)
Mutual labels:  hyperparameter-optimization, automl
codeflare
Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.
Stars: ✭ 163 (+757.89%)
Mutual labels:  hyperparameter-optimization, automl
yarll
Combining deep learning and reinforcement learning.
Stars: ✭ 84 (+342.11%)
Mutual labels:  deep-reinforcement-learning, soft-actor-critic
learning-to-drive-in-5-minutes
Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes
Stars: ✭ 227 (+1094.74%)
Mutual labels:  sac, soft-actor-critic

Meta-SAC

Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient.
arXiv link

Yufei Wang*, Tianwei Ni*. In 7th ICML AutoML workshop, 2020.
(* indicates equal contribution)

PyTorch implementation of Meta-SAC and baselines.

Requirements

  • PyTorch 1.4+
  • OpenAI Gym
  • Mujoco

Usage

  • Meta-SAC: meta_sac directory
  • SAC-v1, SAC-v2: sac directory
  • TD3: TD3 directory

Reference

pytorch-soft-actor-critic

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].