Gymnasium
episodic-transformer-memory-ppo
Gymnasium | episodic-transformer-memory-ppo | |
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12 | 5 | |
5,759 | 109 | |
5.2% | - | |
9.3 | 2.5 | |
7 days ago | about 1 month ago | |
Python | Python | |
MIT License | MIT License |
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Gymnasium
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NASA JPL Open Source Rover That Runs ROS 2
"Show HN: Ghidra Plays Mario" (2023) https://news.ycombinator.com/item?id=37475761 :
[RL, MuZero reduxxxx ]
> Farama-Foundation/Gymnasium is a fork of OpenAI/gym and it has support for additional Environments like MuJoCo: https://github.com/Farama-Foundation/Gymnasium#environments
> Farama-Foundatiom/MO-Gymnasiun: "Multi-objective Gymnasium environments for reinforcement learning": https://github.com/Farama-Foundation/MO-Gymnasium
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Show HN: Ghidra Plays Mario
https://github.com/Farama-Foundation/Gymnasium#environments
Farama-Foundatiom/MO-Gymnasiun:
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Are there any AI projects that plays a game for you and learns?
https://github.com/Farama-Foundation/Gymnasium - A framework Python library to build and train your own AI to play games
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Unstable SAC training of sparse-reward task
The only change in the environment from the one here is the reward function which is given its return value using the following code snippet (replacing lines 648-672 in the above url):
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Any resources on experiments simulated environments?
This may be useful: https://github.com/Farama-Foundation/Gymnasium
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What's the most challenging Gym environment?
Here are all the environments. So for example, if instead of Hopper-v2 you want the acrobat environment from classic control you can write: env = gym.make('Acrobot-v1')
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Gymnasium 0.28 is now released
This release also includes a large number of documentation updates, minor bug fixes, and other minor improvements; the full release notes are available here if you’d like to learn more: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.28.0.
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TransformerXL + PPO Baseline + MemoryGym
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.
- Gymnasium 0.27 - the first new version since Gymnasium was announced - is now released. It has almost no breaking changes.
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[N] Gymnasium 0.27 - the first new version since Gymnasium was announced - is now released. It has almost no breaking changes.
You can read the release notes here: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.27.0. You can upgrade from 0.26 without any changes unless you're doing something very uncommon; this is how releases will generally be going forward.
episodic-transformer-memory-ppo
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Question about Transformer model input in RL
Check out this implementation https://github.com/MarcoMeter/episodic-transformer-memory-ppo
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Using transformers in RL?
Maybe this easy-to-follow baseline implementation of PPO + TransformerXL is an inspiration for you.
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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.
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Trained a Transformer Decoder architecture with PPO, best way to maximize the entropy?
You can also checkout my baseline implementation of PPO + TrXL.
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TransformerXL + PPO Baseline + MemoryGym
We finally completed a lightweight implementation of a memory-based agent using PPO and TransformerXL (and Gated TransformerXL).
What are some alternatives?
flake8 - The official GitHub mirror of https://gitlab.com/pycqa/flake8
godot_rl_agents - An Open Source package that allows video game creators, AI researchers and hobbyists the opportunity to learn complex behaviors for their Non Player Characters or agents
Flake8-pyproject - Flake8 plug-in loading the configuration from pyproject.toml
popgym - Partially Observable Process Gym
ruff - An extremely fast Python linter and code formatter, written in Rust.
recurrent-ppo-truncated-bptt - Baseline implementation of recurrent PPO using truncated BPTT
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
brain-agent - Brain Agent for Large-Scale and Multi-Task Agent Learning
Visual Studio Code - Visual Studio Code
rl8 - A high throughput, end-to-end RL library for infinite horizon tasks.
flake8
DI-engine - OpenDILab Decision AI Engine