pytorch-a2c-ppo-acktr-gail
DI-engine
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| pytorch-a2c-ppo-acktr-gail | DI-engine | |
|---|---|---|
| 3 | 3 | |
| 3,423 | 2,553 | |
| - | 4.2% | |
| 0.0 | 8.7 | |
| almost 2 years ago | 5 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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pytorch-a2c-ppo-acktr-gail
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How does advantage estimation is done when episodes are of variable length in PPO?
As an example look at "compute_returns" function here (and pay attention to how self.masks is used): https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail/blob/master/a2c_ppo_acktr/storage.py
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How to pretrain a model on expert data?
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
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Trying to Train PPO Agent for Pendulum-v0 from Pixel Inputs
For the PPO, I used this repo, which includes most tricks including GAE, normalized rewards, etc. I have verified this repo works for the traditional Pendulum-v0 task and Atari games (Pong and Breakout).
DI-engine
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Anyone have experience with DI-Engine?
I posted a while back asking people what frameworks they were using for RL research. Recently i stumbled upon DI-Engine which looks promising! Actively maintained, with a diverse set of algorithms already implemented.
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TransformerXL + PPO Baseline + MemoryGym
DI Engine
- Struggling with algorithm generality? Try DI engine; here is the solution
What are some alternatives?
soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
tianshou - An elegant PyTorch deep reinforcement learning library.
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
on-policy - This is the official implementation of Multi-Agent PPO (MAPPO).
PCGrad - Code for "Gradient Surgery for Multi-Task Learning"
myosuite - MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.