d3rlpy
pytorch-a2c-ppo-acktr-gail
| d3rlpy | pytorch-a2c-ppo-acktr-gail | |
|---|---|---|
| 2 | 3 | |
| 1,215 | 3,423 | |
| - | - | |
| 9.1 | 0.0 | |
| 11 days ago | almost 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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d3rlpy
- Python libraries for solving reinforcement learning problems implemented in OpenAI gym
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Conservative Q Learning TD error not converging
Hi, I am using the discrete conservative Q learning implementation in the d3rlpy library (https://github.com/takuseno/d3rlpy) to train a policy offline to optimize mechanical ventilation treatment by using the MIMIC-III dataset (https://physionet.org/content/mimiciii-demo/1.4/).
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).
What are some alternatives?
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
exorl - ExORL: Exploratory Data for Offline Reinforcement Learning
soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.
Coursera_Reinforcement_Learning - Coursera Reinforcement Learning Specialization by University of Alberta & Alberta Machine Intelligence Institute
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Minari - A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
rlai - This is a Python implementation of concepts and algorithms described in "Reinforcement Learning: An Introduction" (Sutton and Barto, 2018, 2nd edition).
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
PCGrad - Code for "Gradient Surgery for Multi-Task Learning"
DI-engine - OpenDILab Decision AI Engine