Customized version of the original RSL RL project that additionally supports multi discrete action spaces, providing a fast and simple implementation of PPO algorithm, designed to run fully on GPU.

Code release for "Learning in Complex Action Spaces without Policy Gradients" TMLR (2025)

Pytorch implementation of Proximal Policy Optimization (PPO) for discrete action spaces

Pytorch implementation of Deep Q Network (DQN) learning with vectorized environments

Pytorch implementation of Double Deep Q Network (DDQN) learning with vectorized environments

PyTorch implementation of Monte Carlo policy gradient reinforcement

Deliverables relating to the Advanced Reinforcement Learning University Unit

Mountain Car v0 using Q-Learning

Implementing Deep Reinforcement Learning Algorithms in Python for use in the MuJoCo Physics Simulator

PyTorch implementation of the discrete Soft-Actor-Critic algorithm.

Upside-Down Reinforcement Learning (⅂ꓤ) implementation in PyTorch. Based on the paper published by Jürgen Schmidhuber.