npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

embody

v0.0.5

Published

A digital consciousness training environment

Downloads

1

Vulnerabilities

Powered byPowered by Snyk
  • 0High
  • 0Medium
  • 0Low

Links

Maintainers

piusnyakoojopiusnyakoojo

Keywords

embodydigitalconsciousnessartificialintelligenceembodimentsensoractuatorlearningenvironment

Readme

🌎 embody

npm version downloads coverage pipeline

Demo | Video Tutorial | Paper

embody is a sensor and actuator environment for training digital consciousness (also known as artificial intelligence) algorithms.

This project is a work-in-progress and does not completely work as suggested by this document. Parts of the system work as suggested, other parts are still being worked on.

About

Embody is a set of interfaces to sensors and actuators on a computer. The interfaces provide a way to receive or update data about the state of a computer.

Sensor interfaces retrieve data about the state of a computer. For example: a screen capture video stream, mouse movement events and keyboard press events. Actuator interfaces update the state of a computer. For example: moving the mouse and pressing a keyboard button.

Benefits

  • 💪 Flexible: Learn from across any number of sense, action and interface configurations

Sensor Features

  • 👁️ Sight: See the world through a screen capture video stream, webcam or camera
  • 👂 Hearing: Use a microphone to listen to the world (WIP)
  • 🖐️ Touch: Feel through heat, texture and force feedback sensors (WIP)
  • 👃 Smell: Respond to air quality sensors to model scent (WIP)
  • 👅 Taste: Respond to water quality sensors to model taste (WIP)

Actuator Features

  • 🖼️ Imagination: Create images on a 2D canvas by painting with pixels (WIP)
  • 🙌 Movement: Move in the world using a mouse, keyboard or motor
  • 👄 Speech: Create voice patterns to be played by speakers (WIP)

Limitations

  • 🧪 Experimental: This project is a work-in-progress

Screenshots

Installation

Install the library

npm install embody -g

Example Usecases

API Reference

Documentation

To check out project-related documentation, please visit docs

Contributing

Feel free to join in. All are welcome. Please see contributing guide.

Acknowledgements

Learn More

Related Work

Some well-known artificial intelligence training environments include: Conceptual Learning (VicariousAI PixelWorld), Reinforcement Learning (OpenAI Gym, DeepMind Lab, garage), Algorithm-Agnostic (ROS, Embody)

License

MIT