gym-continuousDoubleAuction
recurrent-ppo-truncated-bptt
| gym-continuousDoubleAuction | recurrent-ppo-truncated-bptt | |
|---|---|---|
| 5 | 6 | |
| 136 | 106 | |
| - | - | |
| 0.0 | 3.2 | |
| over 1 year ago | 6 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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gym-continuousDoubleAuction
recurrent-ppo-truncated-bptt
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What RL library supports custom LSTM and Transformer neural networks to use with algorithms such as PPO?
I provide baseline implementations on TransformerXL + PPO and LSTM/GRU + PPO. These are designed to be slim and easy-to-follow so that you can advance those implementations to the features and toolset that you need.
- How does a recurrent generator work in PPO?
- LSTM encoder in the policy?
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what is the best approach to POMDP environment?
Second, when training a limited view agent in a tabular environment, I expected the rppo agent to perform better than cnn-based ppo. But it didn't. I used this repository that was already implemented and saw slow learning based on this.
- LSTM with SAC not learning well on tasks like Mountain Car and Lunar Lander?
- Recurrent PPO using truncated BPTT
What are some alternatives?
alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
QuantitaveFinanceExamplesPy - Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir).
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
Finding-Alpha-with-AI - A 3 part series of Jupyter notebooks to help one find alpha in the stock market with AI
snakeAI - testing MLP, DQN, PPO, SAC, policy-gradient by snake
FinanceExamplesPy - Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir). [Moved to: https://github.com/mrtkp9993/QuantitaveFinanceExamplesPy]
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
SGX-Full-OrderBook-Tick-Data-Trading-Strategy - Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
neroRL - Deep Reinforcement Learning Framework done with PyTorch
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)