RL-PyT

This repository contains PyTorch implementations of reinforcement learning algorithms. Its purpose is to provide straightforward and easily understandable code for individuals to learn about basic reinforcement learning algorithms.

Current Implementations

1. Deep Q Learning (DQN) _{^{(Mnih et al. 2013)}}
2. D3QN _{^{(Wang et al. 2016)}}
3. Deep Deterministic Policy Gradients (DDPG) _{^{(Lillicrap et al. 2016 )}}
4. Twin Delayed Deep Deterministic Policy Gradients (TD3) _{^{(Fujimoto et al. 2018)}}
5. Soft Actor-Critic (SAC) _{^{(Haarnoja et al. 2018)}}
6. Soft Actor-Critic for Discrete Actions (SAC-Discrete) _{^{(Christodoulou 2019)}}
7. Tsallis Actor-Critic (TAC) _{^{(Lee, Kyungjae, et al. 2019)}}
8. Proximal Policy Optimisation (PPO) _{^{(Schulman et al. 2017)}}