Course (CS6700) assignment on Reinforcement Learning
-
Updated
Apr 29, 2018 - Python
Course (CS6700) assignment on Reinforcement Learning
Reinforcement learning analysis using Python, OpenAI Gym and rllab.
Exercises from Open AI's gym python module
Implemented Deep Reinforcement Learning algorithm (Neural Q-Learning) on a classic control task in OpenAI AI-Gym Environment - the CartPole game
Using Reinforcement Learning (DQN) to train a Lunar Lander for automated landing
Reinforcement Learning Project - Mountain Car
A2C implementation for OpenAI Gym agents
This library is a Deep Q-Learning trainer, specialized for vision models, in various OpenAI Gym environments.
Reinforcement Learning DQN - using OpenAI Cart Pole environment
💥💥 This is a easy installable extension for OpenAi Gym Environment. This simulates SpaceX Falcon landing.
This project provides a comprehensive understanding of reinforcement learning, focusing on Deep Q-Learning (DQN). It involves exploring the OpenAI Gym library, implementing DQN from DeepMind's seminal paper, and enhancing the DQN algorithm for improved performance and stability.
Implement a deep Q-learning network to play a simple game from OpenAI Gym.
Deep Reinforcement Learning gym.
OpenAI polecart challenge implemented with DQN
Implementation of a basic Q Learning algorithm in the OpenAI's gym environment
A solution for LunarLander from OpenAI Gym using deep Q-Learning implemented in python using only tensorflow
Implement dynamic programming to solve an AI frozen lake problem.
Experimenting the OpenAI gym tool for Reinforcement Learning
Add a description, image, and links to the openai-gym topic page so that developers can more easily learn about it.
To associate your repository with the openai-gym topic, visit your repo's landing page and select "manage topics."