pybullet-gym
rl-baselines-zoo
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| pybullet-gym | rl-baselines-zoo | |
|---|---|---|
| 7 | 2 | |
| 810 | 1,106 | |
| - | - | |
| 0.0 | 0.0 | |
| over 2 years ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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pybullet-gym
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Well, at least Epic kinda started "promoting" Rocket League inside Fortnite LUL
And when something like "RL/Fortnite Racing" comes out, with shared inventory, it may work as the pilot "beta test" of RL finally working in UE5. At least the game's physics engine (pybullet.org) is independent of the graphics. https://x.com/CactousMan/status/1690437803711320064
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Mujoco vs Pybullet for closed loop chain environment
From what I know in pybullet you define the system of the environment loading an urdf file. So if you check the InvertedPendulum environment of pybullet I think you could create your desired urdf without a problem. I have not used mujoco, but it seems strange that it could not do what you want to do... Maybe there is a parameter of the joints or some kind of tolerance for the initial position?
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Alternatives to Unity3D for simulating 3D environments with realistic physics for robotics and training a reinforcement learning model?
So far I found PyBullet, RobotPy, RobotDK, SOFA, and some others, but I wonder if there is something that is comparable or better than Unity 3D for this specific use case.
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Getting started in 3D design
yeah, i guess compared to modeling tools like tinkercad, blender is not intuitive and hard to learn. im not aware of any FEM with blender but there's bullet, basis of https://pybullet.org/. blender has an omniverse connector now so it could probably be used in a pipeline with nvidia's isaac. https://developer.nvidia.com/isaac-sim https://developer.nvidia.com/blog/introducing-omniverse-usd-support-for-blender/
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I’m 15 and this is yeet
Programming is also really important when learning anything about machine learning and I would start out with the OpenAI Gym and its derivative for learning some of the simpler algorithms on toy environments that doesn't require a whole lot of computing power. Then you can move on to the more hardware constrained simulators that I mentioned in the previous comment (MuJoCo, PyBullet, NVIDIA Isaac Gym).
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[N] Mujoco is free for everyone until October 31 2021
shout-out to the open-source clones of the mujoco gym environments here
- Ask questions ahead of the Microsoft Research RL AMA on March 24 with John Langford and Akshay Krishnamurthy
rl-baselines-zoo
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Agent trains great with PPO but terrible with SAC --> Advice for Hyperparameters
Take a look at these tuned sets of hyperparameters for various problems in PPO and SAC. The batch sizes are WAY smaller regardless of the problem. Your initial learning rate may also be too high.
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How do I convert zoo / gym trained models to TensorFlow Lite or PyTorch TorchScript?
https://github.com/araffin/rl-baselines-zoo (TensorFlow based, using https://github.com/hill-a/stable-baselines)
What are some alternatives?
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
gym-pybullet-drones - PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
gym_solo - A custom open ai gym environment for solo experimentation.
pytorch-blender - :sweat_drops: Seamless, distributed, real-time integration of Blender into PyTorch data pipelines
rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
gym - A toolkit for developing and comparing reinforcement learning algorithms.