stable-baselines
gym-battleship
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| stable-baselines | gym-battleship | |
|---|---|---|
| 10 | 2 | |
| 4,000 | 9 | |
| - | - | |
| 0.0 | 2.4 | |
| over 1 year ago | 12 months ago | |
| Python | Python | |
| MIT License | MIT License |
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stable-baselines
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Distributed implementation tips
As underlined by gold-panda, you can give a try with multiprocessing. I once implemented a version based on what is done in stable_baselines v1 (https://github.com/hill-a/stable-baselines/blob/master/stable_baselines/common/vec_env/subproc_vec_env.py)
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GAIL without actions?
Found relevant code at https://github.com/hill-a/stable-baselines + all code implementations here
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Best framework to use if learning today
Depends what you wanna do. Universal answer would be https://stable-baselines.readthedocs.io/
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weird mean reward graph
As you will see here it is recommended to augment this safety measure with target kl_divergence, that will ensure even smoother learning and enforce early stopping to prevent learning collapses.
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Nvidia ISAAC gym/RL
Code for https://arxiv.org/abs/1707.06347 found: https://github.com/hill-a/stable-baselines
- Bounds for observation
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Understanding multi agent learning in OpenAI gym and stable-baselines
I haven't read the code, but stable-baselines doesn't support multi-agent environments (https://github.com/hill-a/stable-baselines/issues/423), so I think they're trying to make learning multi-agent easier with Environment.train().
- Using Reinforment Learning to beat the first boss in Dark souls 3 with Proximal Policy Optimization
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Reinforcement Learning Crash Course (Free)
- https://github.com/hill-a/stable-baselines (Tensorflow)
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JAX Implementations of Actor-Critic Algorithms
- tf2 speed: https://github.com/hill-a/stable-baselines/issues/576#issuecomment-573331715
gym-battleship
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Battleship
There are a few gyms for battleship, https://github.com/thomashirtz/gym-battleship ... some variations I would like to see involve a much bigger grid (100x100) and moving ships along axis @ various rates ... but then you would get a different game I guess.
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Python OpenAI Gym environment for reinforcement learning
(shamless plug) If you want to check out a simple custom gym environment of a boardgame, I did a battleship env some time ago: https://github.com/thomashirtz/gym-battleship
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
rl-baselines-zoo - A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Tic-Tac-Toe-Gym - This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning
portfolio-management - Repository for portfolio management using Pytorch, SQLAlchemy and XArray. The management is done using the reinforcement learning algorithm "Soft Actor-Critic".
DI-engine - OpenDILab Decision AI Engine
ideas - :rocket: Ideas for everyone under a CC licence. Feel free to use. I'll send you a postcard if you build anything on this list.