|7 months ago||6 days ago|
|MIT License||GNU General Public License v3.0 or later|
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.
Live2D characters from Konosuba Fantastic Days (Details and download in comments)
2 projects | /r/Megumin | 28 Aug 2021
I actually used this application which automatically does it for you from the game files https://github.com/Perfare/UnityLive2DExtractor
At least I put effort into the AI prompt to generate some code that people can refer to, whereas you do absolutely nothing to contribute to the community.
2 projects | /r/programmingcirclejerk | 8 May 2023
and PR content: https://github.com/Unity-Technologies/ml-agents/commit/ed212103e451449bf84711a4a8f7bf11dfb1211a2 projects | /r/programmingcirclejerk | 8 May 2023
TransformerXL + PPO Baseline + MemoryGym
10 projects | /r/reinforcementlearning | 15 Feb 2023
Thanks! It really depends on the task that you want to implement. But in general, sticking to the standard gymnasium API is important. If you want to implement a 2D environment then PyGame is promising. If it's more like a game, check out Unity ML-Agents or Godot RL Agents. Anything simpler can also be just pure python code. You also need to carefully design your observation space, action space and reward function. My advice is to explore design choices of related environments.
Impact of using sockets to communicate between Python and RL environment
2 projects | /r/reinforcementlearning | 2 Oct 2022
When looking into implementing RL in a game environment, I found that both Unity MLAgents and the third-party UnrealCV communicate between the game environments and Python using sockets. I am looking into implementing RL for Unreal and wondering about the performance impact of using sockets vs using RL C++ libraries to keep everything "in-engine"/native.
After 8 Hours, my ML Agents learned how to work together!
2 projects | /r/Unity3D | 1 Jul 2022
For the last question, I suggest downloading this example package and taking a look at the Soccer example. It shows how to have 2 completely different Agents on different teams learn from each other.2 projects | /r/Unity3D | 1 Jul 2022
What helped me the most to get started was this youtube video, and then after that I would recommend going through the official unity github examples and their scenes to understand how they approached different tasks.
I'm failing to download a repository correctly
2 projects | /r/u_No_Possibility_7588 | 18 Jan 2022
# Install steps - download the `ml-agents` repository `git clone https://github.com/Unity-Technologies/ml-agents` - create a Python folder in `ml-agents` and clone `social_rl` repo into it `svn export https://github.com/google-research/google-research/trunk/social_rl` - copy `environments.py` and `gymwrappers.py` into this Python folder - create a python3.8 environment and install `social_rl` requirements `conda create -n mlagents python=3.8` `pip install -r requirements.txt` - install `ml-agents_envs`, `ml-agents` and `gym-unity` from the `ml-agents` repository `python install setup.py`
8+ Reinforcement Learning Project Ideas
8 projects | dev.to | 30 Sep 2021
Unity ML-Agents is a relatively new add-on to the Unity game engine. It allows game developers to train intelligent NPCs for games and enables researchers to create graphics- and physics-rich RL environments. Project ideas to explore include:
How to train agents to play volleyball using deep reinforcement learning
2 projects | dev.to | 22 Sep 2021
Descriptions of the configurations are available in the ML-Agents official documentation.
🏐 Ultimate Volleyball: A 3D Volleyball environment built using Unity ML-Agents
3 projects | dev.to | 10 Aug 2021
Inspired by Slime Volleyball Gym, I built a 3D Volleyball environment using Unity's ML-Agents toolkit. The full project is open-source and available at: 🏐 Ultimate Volleyball.
What are some alternatives?
UtinyRipper - GUI and API library to work with Engine assets, serialized and bundle files
AssetStudio - AssetStudio is a tool for exploring, extracting and exporting assets and assetbundles.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
carla - Open-source simulator for autonomous driving research.
unity-avatar-generation - A minimal example of how to use Unity's AvatarBuilder.BuildHumanAvatar API.
ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents
tensortrade - An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
recurrent-ppo-truncated-bptt - Baseline implementation of recurrent PPO using truncated BPTT
Il2CppDumper - Unity il2cpp reverse engineer
google-research - Google Research