slimevolleygym
ml-agents
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slimevolleygym | ml-agents | |
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3 | 60 | |
698 | 16,324 | |
- | 1.7% | |
3.2 | 8.1 | |
5 months ago | 10 days ago | |
Python | C# | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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slimevolleygym
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How to train multi agents with PPO/DQN for playing Atari Game
This is a good example for self-play training Slime Volleyball
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RL framework for 2v2 kart soccer
Hi great that you are interested in the area, but as a beginner project is quite complex, having a team is a multi-agent task so not a small feat and i guess you want the same policy to play against itself? what is know as selfplay. which is not so hard to understand but a little bit in the tech part. Look a this 1v1 environment has a tutorial where they show selfplay and other single agent approaches using a well known RL Pytorch implementations. and for the policy optimization algorithm as the tutorial before you should go with PPO (which is a on-policy method like reinforce). there is something called HER for sparse reward but it works with off-policy methods like ddpg or sac. read a little bit more about this and then you will get the idea. My suggestion if you dont have extend experience try a supervise learning approach, where you have a dataset where the action is the label to be predicted and the observation is the input, MSE for the loss. like predicting the stering wheel angle from the image of the road kind of setup.
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🏐 Ultimate Volleyball: A 3D Volleyball environment built using Unity ML-Agents
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.
ml-agents
- How do I change the maximum number of steps for training
- are the install steps update to date?
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Help with regenerating new worker id
I am a beginner to using ML Agents to simulate an environment for DL i am trying to trial runs by tinkering through different values between the action space and keep encountering this issue when attempting to run a new trial. I've tried mlagents-learn --force and mlagents-learn --run-id=newtest but both prompt the same error message. Using linux, I am aware of a similar bug occuring in older versions (https://github.com/Unity-Technologies/ml-agents/issues/1505) but solutions didn't fix it.
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Trying to get into AI
The Github page for ML-Agents has a fairly straight forward example.
- Implement API to allow AI/ML to play your game, or is it not needed?
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Is there a good alternative to Unity ML Agents?
Very few commits in the last year and not many new features (https://github.com/Unity-Technologies/ml-agents/commits/develop)
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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.
and PR content: https://github.com/Unity-Technologies/ml-agents/commit/ed212103e451449bf84711a4a8f7bf11dfb1211a
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I have some questions as an absolute beginner.
Unity can build a stand-alone application or be used as a library. Javascript is deprecated, and Boo along with it although it was never really supported to begin with. Various types of machine learning are supported through the ML-Agent Toolkit and pretty well documented. The toolkit has a Python API but you should be careful about doing anything too unusual in Unity because the documentation tends to have a lot of dead-ends.
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Could Somebody please help me figure this out ? been struggling with it for a week now
Op, I'd just pull the repo again to a new folder from https://github.com/Unity-Technologies/ml-agents (use SourceTree for simplicity if you don't know git).
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Unity ML-Agents documentation is wrong, I can't build an executable and run training as the docs state
My github issue on their documentation: https://github.com/Unity-Technologies/ml-agents/issues/5899
What are some alternatives?
ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents
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.
AssetStudio - AssetStudio is a tool for exploring, extracting and exporting assets and assetbundles.
unity-avatar-generation - A minimal example of how to use Unity's AvatarBuilder.BuildHumanAvatar API.
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
MediaPipeUnityPlugin - Unity plugin to run MediaPipe
google-research - Google Research
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.