Playing around reinforcement learning algorithms
This is a project acompanies my catching of the recent years developements in the Reinforecement learning domain. It gathers simple implementations of state-of-art RL algorithms under the same API.
- DQN: With variants (Double, Dueling PriorityMemory, NoisyNets)
- VanilaPG
- A2C
- PPO: With value and norm clipping variants
- DDPG
- TD3
- ICM: In progress
- Evolution Methods: (ES CEM Etc..) Todo
Agent are sorted by the the action space types they can work with: Discrete, Continuous and Hybrid (Both)
- All discrete agents
- TD3
- PPO
- PPO: Agent can land but does'n larn to stop using throtle and get the final bonus
- DDPG: soved in ~900 epsiodes
- TD3:
- TD3 fine tuned from agent trained on BipedalWalker)
Credit to all those Github repository I aspired from. I consulted a lot of repositories in order while implementing the algorithms, defining architectures and finetuning hyperparameters
- https://github.com/sfujim/TD3.git
- https://github.com/iKintosh/DQN-breakout-Pytorch.git
- https://github.com/Anjum48/rl-examples.git
- https://github.com/chagmgang/pytorch_ppo_rl.git
- https://github.com/shivaverma/OpenAIGym.git
- https://github.com/plopd/deep-reinforcement-learning.git
- https://github.com/adik993/ppo-pytorch.git
- https://github.com/higgsfield/RL-Adventure.git
- https://github.com/Adriel-M/OpenAI-Gym-Solutions.git
- https://github.com/nikhilbarhate99/PPO-PyTorch.git