or-gym
pytorch-a2c-ppo-acktr-gail
| or-gym | pytorch-a2c-ppo-acktr-gail | |
|---|---|---|
| 2 | 3 | |
| 355 | 3,423 | |
| - | - | |
| 0.0 | 0.0 | |
| 7 months ago | almost 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
or-gym
-
Gym like frameworks for combinatorial optimization on Graphs?
How about ORGym: https://github.com/hubbs5/or-gym ?
-
Is there a reinforcement learning method to find stock policy for single echelon inventory system ?
Specifically, inputs to I0 through L should be 1-column arrays: https://github.com/hubbs5/or-gym/blob/d5fbc73623c7b197316d33fba094105953889df3/or_gym/envs/supply_chain/inventory_management.py#L46
pytorch-a2c-ppo-acktr-gail
-
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
-
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.
-
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?
ml4vrp - Geometric Deep Learning Models for Vehicle Routing Problem
soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.
maro - Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
NLNS - Neural Large Neighborhood Search for the Capacitated Vehicle Routing Problem
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
DeepBeerInventory-RL - The code for the SRDQN algorithm to train an agent for the beer game problem
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
OpenGraphGym
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