ml-agents
recurrent-ppo-truncated-bptt
| ml-agents | recurrent-ppo-truncated-bptt | |
|---|---|---|
| 60 | 6 | |
| 16,394 | 106 | |
| 1.0% | - | |
| 8.0 | 3.2 | |
| 5 days ago | 9 days ago | |
| C# | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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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
recurrent-ppo-truncated-bptt
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What RL library supports custom LSTM and Transformer neural networks to use with algorithms such as PPO?
I provide baseline implementations on TransformerXL + PPO and LSTM/GRU + PPO. These are designed to be slim and easy-to-follow so that you can advance those implementations to the features and toolset that you need.
- How does a recurrent generator work in PPO?
- LSTM encoder in the policy?
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what is the best approach to POMDP environment?
Second, when training a limited view agent in a tabular environment, I expected the rppo agent to perform better than cnn-based ppo. But it didn't. I used this repository that was already implemented and saw slow learning based on this.
- LSTM with SAC not learning well on tasks like Mountain Car and Lunar Lander?
- Recurrent PPO using truncated BPTT
What are some alternatives?
gym - A toolkit for developing and comparing reinforcement learning algorithms.
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
snakeAI - testing MLP, DQN, PPO, SAC, policy-gradient by snake
carla - Open-source simulator for autonomous driving research.
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
AssetStudio - AssetStudio is a tool for exploring, extracting and exporting assets and assetbundles.
neroRL - Deep Reinforcement Learning Framework done with PyTorch
unity-avatar-generation - A minimal example of how to use Unity's AvatarBuilder.BuildHumanAvatar API.
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)