Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

This Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.

Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023

Minimal implementation of the network layers of the paper "Noisy Networks for Exploration" using Pytorch.

심층강화학습기반 장애물과 신호등을 고려한 다차선 자율주행 연구 (한국통신학회 논문지 2024-6월호)

Slide presentation reviewing advances in reinforcement learning

Example Noisy DQN implementation with ReLAx

Deep Reinforcement Learning containing 1) DQN 2) Double DQN 3) Dueling DQN 4) Noisy Net (Noisy DQN) 5) DQN with Prioritized Experience Replay 6) Noisy Double DQN with Prioritized Experience Replay 7) Noisy Dueling Double DQN with Prioritized Experience Replay