Deep reinforcement learning solution for some open AI gym environments.
-
Updated
May 21, 2018 - Python
Deep reinforcement learning solution for some open AI gym environments.
Agents for reinforcement learning tasks.
Solution to the Deep RL Bootcamp labs from UC Berkeley
Inducing hierarchy via models and trajectories
Beer Game implemented as an OpenAI gym environment.
Implementation of hill-climbing and policy gradient RL algorithms on OpenAI Gym Cartpole environment as part of OpenAI Requests for Research.
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
This project inolved applied Reinfocrcement learnging viz,. Deep Q Learning for the 'cart' to learn to balance the 'pole'
Reinforcement Learning Agents Trained in the CARLA Simulator
Implementing Deep Q Network and its improvement techniques using Pytorch
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
Using Reinforcement Learning to solve Maze Navigation, Acrobot, Mountain Car
Course work of Reinforcement-Learning-CS6700
💳 Creates a new gym environment for credit-card anomaly detection using Deep Q-Networks (DQN) and leverages Open AI's Gym toolkit to allocate appropriate awards to the RL agent.
A customised Open-AI gym environment which simulate the puzzle video game Threes
I am trying to implement various AI algorithms on various environments (like OpenAI-gym) as I learned my toward the safe AI
Implementation of REINFORCE for open ai env acrobot, epsilon greedy Q-Learning for open ai env taxi & TD(0) for custom gameshow env KBC.
Add a description, image, and links to the open-ai-gym topic page so that developers can more easily learn about it.
To associate your repository with the open-ai-gym topic, visit your repo's landing page and select "manage topics."