recurrent-ppo-truncated-bptt
snakeAI
| recurrent-ppo-truncated-bptt | snakeAI | |
|---|---|---|
| 6 | 1 | |
| 106 | 10 | |
| - | - | |
| 3.2 | 5.5 | |
| 12 days ago | 2 months ago | |
| Jupyter Notebook | C++ | |
| MIT License | - |
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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
snakeAI
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[D] How does Deep Reinforcement Learning remove the need to map or explore every state, action pair for an agent?
i am not very good at machine learning, here's my project https://github.com/WorldEditor50/snakeAI/tree/master/snakeAI, i hope it can help you.
What are some alternatives?
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.
Reinforcement-Learning - Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
torchRL - TorchRL is a C++ reinforcement library using PyTorch C++ backend LibTorch
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
tianshou - An elegant PyTorch deep reinforcement learning library.
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)
ppo-implementation-details - The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization
popgym - Partially Observable Process Gym
episodic-transformer-memory-ppo - Clean baseline implementation of PPO using an episodic TransformerXL memory