git clone udacity-deep-reinforcement-learning_-_2018-07-07_15-22-23.bundle -b master
This repository contains material related to Udacity's Deep Reinforcement Learning Nanodegree program.
The tutorials lead you through implementing various algorithms in reinforcement learning. All of the code is in PyTorch (v0.4) and Python 3.
The labs and projects can be found below. All of the projects use rich simulation environments from Unity ML-Agents. In the Deep Reinforcement Learning Nanodegree program, the projects are reviewed by Udacity experts. These reviews are meant to give you personalized feedback and to tell you what can be improved in your code.
Acrobot-v1with Tile Coding and Q-Learning
Cartpole-v0with Hill Climbing | solved in 13 episodes
Cartpole-v0with REINFORCE | solved in 691 episodes
MountainCarContinuous-v0with Cross-Entropy Method | solved in 47 iterations
MountainCar-v0with Uniform-Grid Discretization and Q-Learning | solved in <50000 episodes
Pendulum-v0with Deep Deterministic Policy Gradients (DDPG)
BipedalWalker-v2with Deep Deterministic Policy Gradients (DDPG)
CarRacing-v0with Deep Q-Networks (DQN) | Coming soon!
LunarLander-v2with Deep Q-Networks (DQN) | solved in 1504 episodes
FrozenLake-v0with Dynamic Programming
Blackjack-v0with Monte Carlo Methods
CliffWalking-v0with Temporal-Difference Methods
To set up your python environment to run the code in this repository, follow the instructions below.
Create (and activate) a new environment with Python 3.6.
bashconda create --name drlnd python=3.6source activate drlnd
bashconda create --name drlnd python=3.6 activate drlnd
Follow the instructions in this repository to perform a minimal install of OpenAI gym.
Clone the repository (if you haven't already!), and navigate to the
python/ folder. Then, install several dependencies.
bashgit clone https://github.com/udacity/deep-reinforcement-learning.gitcd deep-reinforcement-learning/pythonpip install .
Create an IPython kernel for the
bashpython -m ipykernel install --user --name drlnd --display-name "drlnd"
Before running code in a notebook, change the kernel to match the
drlnd environment by using the drop-down
Come learn with us in the Deep Reinforcement Learning Nanodegree program at Udacity!