dongminlee94 / Samsung Drl Code
Repository for codes of Deep Reinforcement Learning (DRL) lectured at Samsung
Stars: ✭ 99
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Samsung Drl Code
Max
Code for reproducing experiments in Model-Based Active Exploration, ICML 2019
Stars: ✭ 61 (-38.38%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Rl Course Experiments
Stars: ✭ 73 (-26.26%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Drl papernotes
Notes and comments about Deep Reinforcement Learning papers
Stars: ✭ 65 (-34.34%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Pytorch sac ae
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
Stars: ✭ 94 (-5.05%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Awesome Deep Reinforcement Learning
Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...
Stars: ✭ 95 (-4.04%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Ml In Tf
Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!
Stars: ✭ 45 (-54.55%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Torch Ac
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
Stars: ✭ 70 (-29.29%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deep Q Learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Stars: ✭ 1,013 (+923.23%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Rlenv.directory
Explore and find reinforcement learning environments in a list of 150+ open source environments.
Stars: ✭ 79 (-20.2%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Cs234 Reinforcement Learning Winter 2019
My Solutions of Assignments of CS234: Reinforcement Learning Winter 2019
Stars: ✭ 93 (-6.06%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deep Learning Drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Stars: ✭ 9,717 (+9715.15%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Async Deeprl
Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning
Stars: ✭ 44 (-55.56%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Mujocounity
Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).
Stars: ✭ 47 (-52.53%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deterministic Gail Pytorch
PyTorch implementation of Deterministic Generative Adversarial Imitation Learning (GAIL) for Off Policy learning
Stars: ✭ 44 (-55.56%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
1 Year Machinelearning Journey
An advanced program in Machine Learning and Deep Learning
Stars: ✭ 69 (-30.3%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deepqlearning.jl
Implementation of the Deep Q-learning algorithm to solve MDPs
Stars: ✭ 38 (-61.62%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deepbootcamp
Solved lab problems, slides and notes of the Deep Reinforcement Learning bootcamp 2017 held at UCBerkeley
Stars: ✭ 39 (-60.61%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Muzero General
MuZero
Stars: ✭ 1,187 (+1098.99%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Snake
Artificial intelligence for the Snake game.
Stars: ✭ 1,241 (+1153.54%)
Mutual labels: reinforcement-learning, deep-reinforcement-learning
Deep Reinforcement Learning, Summer 2019 (Samsung)
This repository contains codes for Deep Reinforcement Learning (DRL) algorithms with PyTorch (v0.4.1). It also provides lecture slides that explain codes in detail.
The agents with the DRL algorithms have been implemented and trained using classic control environments in OpenAI Gym.
Table of Contents
00. Prerequisite
01. Deep Learning with PyTorch
02. Deep Q-Network (DQN) & Double DQN (DDQN)
03. Advantage Actor-Critic (A2C) & Deep Deterministic Policy Gradient (DDPG)
04. Trust Region Policy Optimization (TRPO) & Proximal Policy Optimization (PPO)
05. Soft Actor-Critic (SAC)
Learning curve
CartPole
Pendulum
Paper
- Deep Q-Network (DQN)
- Double DQN (DDQN)
- Advantage Actor-Critic (A2C)
- Asynchronous Advantage Actor-Critic (A3C)
- Deep Deterministic Policy Gradient (DDPG)
- Trust Region Policy Optimization (TRPO)
- Generalized Advantage Estimator (GAE)
- Proximal Policy Optimization (PPO)
- Soft Actor-Critic (SAC)
Reference
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].