1. RlcycleA library for ready-made reinforcement learning agents and reusable components for neat prototyping
2. Policy Gradient MethodsImplementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
3. deep-Q-networksImplementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
5. distributedRLA framework for easy prototyping of distributed reinforcement learning algorithms