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

Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.

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

The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.

Deep Reinforcement learning based tumour localisation

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.

Deliverables relating to the Advanced Reinforcement Learning University Unit

Implementation of Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings (NeurIPS, 2021) in Python

Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.

Pytorch implementation of Deep Deterministic Policy Gradients (DDPG)

Pytorch implementation of twin delayed deep deterministic policy gradients (TD3)

PPO algorithm implemetation for TF 2.8.0

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