modelicagym
Minigrid
| modelicagym | Minigrid | |
|---|---|---|
| 1 | 8 | |
| 73 | 2,008 | |
| - | 0.4% | |
| 0.0 | 6.9 | |
| almost 2 years ago | 10 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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modelicagym
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control libraries for python
Modelica-gym can be used if you are implementing model separately in Modelica language
Minigrid
- Environments that require long-term memory and reasoning
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Best GridWorld environment?
If you want something as simple as possible, I'd go with MiniGrid, and if you want to have a richer world with more complex settings, then MiniHack.
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Using FastAI to navigate matterport spaces?
This is a pretty hard domain to start with as someone "brand new" to AI. If you're interested in the vision aspect, I'd suggest you start by training a DNN for the CIFAR-10 task. There are plenty of tutorials out there. If you're more interested in the navigation aspect, you could start by training a Q-learning agent to solve some of the simpler problems in gym-minigrid.
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How to train an agent in custom mini-grid environment using stable baselines3?
Hello guys I tried to build a custom environment using maxicymeb repo
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What OpenAI Gym environments are your favourite for learning RL algorithms?
For learning and experimentation with RL algorithms, I suggest using a grid world implementation: observations are simple enough (most implementations have a one-hot layered observation) that you do not need deep conv layers to learn complex visual features. You can also make grid worlds as simple or as complex as you like by adding enemies, objects, key-door pairs, changing the size of the grid or decreasing observation radius, etc. There is a reason they are commonly used in research.
- RL environment for hard exploration (infinite) task
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[R] Are there any paper about reinforcement learning solving mazes?
Take a look at: https://github.com/maximecb/gym-minigrid
What are some alternatives?
ns3-gym - ns3-gym - The Playground for Reinforcement Learning in Networking Research
pytorch-blender - :sweat_drops: Seamless, distributed, real-time integration of Blender into PyTorch data pipelines
robo-gym - An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots.
MinAtar
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.
gym-hybrid - Collection of OpenAI parametrized action-space environments.
gym-super-mario-bros - An OpenAI Gym interface to Super Mario Bros. & Super Mario Bros. 2 (Lost Levels) on The NES
space-gym - Challenging reinforcement learning environments with locomotion tasks in space
ma-gym - A collection of multi agent environments based on OpenAI gym.
gym-cartpole-swingup - A simple, continuous-control environment for OpenAI Gym
marlgrid - Gridworld for MARL experiments