Popular GitHub Repositories for Iqn

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Deep Reinforcement Learning codes for study. Currently, there are only codes for algorithms: DQN, C51, QR-DQN, IQN, QUOTA.

A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.

Distributed Rainbow-IQN for Atari

TD3, SAC, IQN, Rainbow, PPO, Ape-X and etc. in TF1.x

PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN

General-Purpose Reinforcement Learning

A TF2.0 implementation of RL baselines.

Durham University, Dissertation: 1st - 92. Additional Materials and Codebase for the paper: Combining Recent Advances in Reinforcement Learning for Super Mario Bros. - Recurrent Replay Deeper Denser Distributed DQN+ (R2D4+).

Distributed PyTorch implementation of D4PG with ray. Using a SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.