A collection of Deep Reinforcement Learning algorithms implemented in tensorflow. Very extensible. High performing DQN implementation.
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Updated
Apr 1, 2017 - Python
A collection of Deep Reinforcement Learning algorithms implemented in tensorflow. Very extensible. High performing DQN implementation.
Solutions to the Deep RL Bootcamp labs
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Deep Feature Extraction for Sample-Efficient Reinforcement Learning
Implementation of some reinforcement learning algorithms
Arduino project for controlling digital WWA LED strips to act as car DRL and sequential turn signals.
a ROS package to turn your point clouds into a simulator for training DRL agents
Atari-DRQN (keras ver.)
Third Project from the Collaboration and Competition Lesson
Solution to the Deep RL Bootcamp labs from UC Berkeley
Multiagent Reinforcement Learning project to handle collaborate and compete scenarios for Tennis Unity environment. MADDPG algorithm is used to solve the environment.
Deep Q Learning for the Banana collection Navigation project - Udacity Nanodegree
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
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