godot_rl_agents
Miniworld
| godot_rl_agents | Miniworld | |
|---|---|---|
| 5 | 3 | |
| 748 | 671 | |
| - | 1.0% | |
| 9.1 | 3.5 | |
| 22 days ago | 23 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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godot_rl_agents
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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.
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An orb learns to dodge obstacles, collect other orbs and reach the end platform by itself using PPO RL AI
1. You will need to setup a virtual environment in python, install the module with pip, and run the "gdrl" command. Then to use it with godot, simply add a "sync" node provided with the plugin to the tree and it will take care of all your agents and their communication with the python module. The agent needs to be in the "AGENT" group and have 3 compulsory variables and some compulsory functions. You can check it out here: Custom Environment .
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Godot Engine Release Management: 4.0 and beyond
I really want to play with Godot RL Agents but I want to do vision based learning and that’s a bit down their road map. If anyone wants to contribute to add that feature I’d love you!
https://github.com/edbeeching/godot_rl_agents
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Build custom 3D gridworld environments
Check out Godot RL Agents as an alternative to Unity.
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[P] Introducing Godot RL Agents
We are proud to announce the release v0.1 of the Godot RL Agents framework, a Deep Reinforcement Learning interface for the Godot Game Engine.
Miniworld
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Miniworld is now mature within the Farama Foundation
Miniworld - a minimalistic 3D interior environment simulator for reinforcement learning & robotics research that allows environments to be easily edited - has now reached the mature inside Farama. You can check out the documentation at https://miniworld.farama.org, and the release notes for all the changes we’ve made to the project at https://github.com/Farama-Foundation/Miniworld/releases/tag/2.0.1.
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Build custom 3D gridworld environments
Have you checked out mini world? https://github.com/maximecb/gym-miniworld
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Training Data
i'm pretty new to this kind of learning task and i found hard to understand some base concepts. I'm studying the Decision Transformer paper and for an university problem i need to train that model using the MiniWorld environment.
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
episodic-transformer-memory-ppo - Clean baseline implementation of PPO using an episodic TransformerXL memory
simglucose - A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose
DI-engine - OpenDILab Decision AI Engine
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Gymnasium - An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
avalon - A 3D video game environment and benchmark designed from scratch for reinforcement learning research
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.