Gym is a toolkit for developing and comparing reinforcement learning algorithms.

💥💥 This is a easy installable extension for OpenAi Gym Environment. This simulates SpaceX Falcon landing.

Explore Q Learning with the Frozen Lake Environment 🥶 in Android.

Using a deep Q-learning network and searching for optimal hyperparameters in order to solve the lunar lander problem provided by OpenAI Gym.

Contains code for Udacity's Deep Reinforcement learning Nanodegree program. The projects consist of experiments and implementations of DQN and DDPG algorithms using PyTorch, OpenAI Gym and UnityML Agents.

Custom environment for OpenAI gym

My bachelor thesis in Bioinformatics

OpenAI Gym environments for classic (nonlinear) problems

In this project, we aim to balance the pole in OpenAI's Gym, Cartpole environment using different Deep Learning techniques.

OpenAI Gym for basketball game

Clear explanations and simple implementations of Deep reinforcement learning Algorithms

There are four designated locations in the grid world indicated by R(ed), B(lue), G(reen), and Y(ellow). When the episode starts, the taxi starts off at a random square and the passenger is at a random location. The taxi drive to the passenger's location, pick up the passenger, drive to the passenger's destination (another one of the four specif…

This is the example to create the gif from the gym openai

Gym Armed Bandits is an environment bundle for OpenAI Gym

An Open AI Gym custom environment

Repository for a custom OpenAI Gym compatible environment for the Parrot Drone ANAFI 4K.

A Taxi driver agent that learns using Q learning and Sarsa

In Cartpole Reinforcement Learning Environment, DQN, DDQN, and Dueling DQN methods are trained respectively.

Tutorial for Pybullet