piSTAR Lab Documentation
piSTAR Lab is in early development.
Who is piSTAR Lab for?
- AI Enthusiasts and Students:
Have fun experimenting with state-of-the-art AI Agents. No coding required.
Gain a better intuition about reinforcement learning by creating your own agents.
- Reinforcement Learning Researchers and Engineers:
Showcase your algorithms by creating extensions for other users to enjoy. No restrictive framework/library requirements.
Import your externally trained agents.
Use piSTAR Lab in your development workflow.
Try your algorithm on newly available environments with just a few clicks
- Game and Environment Developers:
Create Extensions” which make your game playable by piSTAR Agents.
Train your own Agents for your game’s AI
Extension System for adding new agents, environments or tasks types
No framework requirements. Use any framework available in python (other languages coming)
Real-time streaming of observations during training
Single and Multi player environment support
Python API, anything you can do in the UI, you can do in Python as well
Uses Ray Project (https://ray.io/) under the hood for distributed processing
Coming soon (unordered)
Simpler installation and better support for Windows and Mac
Easily share your trained agents with friends or publicly
Docker based agents and environments
Remote agents and environments
Data environments for agents with support for learning from offline data
API for Data Interfaces
Support for browser based games and environments so human can interact directly with their agents.
Support for other programming languages
Human control mode for testing environments via the UI
Better workspace integration with VSCode and Jupyter
Testing and quality verification of extensions
piSTAR Lab is Open Source and welcomes your contributions.