Skip to main content

The Lux AI Challenge Season 2

Project description

Lux-Design-2022

PyPI version

Welcome to the Lux AI Challenge Season 2!

The Lux AI Challenge is a competition where competitors design agents to tackle a multi-variable optimization, resource gathering, and allocation problem in a 1v1 scenario against other competitors. In addition to optimization, successful agents must be capable of analyzing their opponents and developing appropriate policies to get the upper hand.

We are currently in beta, so expect unpolished parts and bugs of the engine and visuals.

To get started, go to our Getting Started section. The Beta competition runs until December 6 and submissions are due at 11:59PM UTC on the competition page: https://www.kaggle.com/c/lux-ai-2022-beta/

Make sure to join our community discord at https://discord.gg/aWJt3UAcgn to chat, strategize, and learn with other competitors! We will be posting announcements on the Kaggle Forums and on the discord.

Season 2 specifications can be found here: https://lux-ai.org/specs-2022-beta. These detail how the game works and what rules your agent must abide by.

Interested in Season 1? Check out last year's repository where we received 22,000+ submissions from 1,100+ teams around the world ranging from scripted agents to Deep Reinforcement Learning.

Getting Started

You will need python 3.7 or above installed on your system. Once installed, you can install the Lux AI season 2 environment with

pip install --upgrade luxai2022

To verify your installation, you can run a match with the CLI tool with

luxai2022 my_bot/main.py my_other_bot/main.py -v 2 -o replay.json

This will turn on logging to level 2, and store the replay file at replay.json. For documentation on the luxia2022 tool, see https://github.com/Lux-AI-Challenge/Lux-Design-2022/tree/main/luxai_runner/README.md, which includes details on how to run a local tournament to mass evaluate your agents.

Each programming language has a starter kit, you can find general API documentation here: https://github.com/Lux-AI-Challenge/Lux-Design-2022/tree/main/kits

The kits folder in this repository holds all of the available starter kits you can use to start competing and building an AI agent. The readme shows you how to get started with your language of choice and run a match. We strongly recommend reading through the documentation for your language of choice in the links below

  • Python
  • C++
  • Javascript - TBA
  • Typescript - TBA
  • Java - TBA

Want to use another language but it's not supported? Feel free to suggest that language to our issues or even better, create a starter kit for the community to use and make a PR to this repository. See our CONTRIBUTING.md document for more information on this.

To stay up to date on changes and updates to the competition and the engine, watch for announcements on the forums or the Discord. See ChangeLog.md for a full change log.

Community Tools

As the community builds tools for the competition, we will post them here!

Contributing

See the guide on contributing

Sponsors

To be announced at the official release.

Core Contributors

We like to extend thanks to some of our early core contributors @duanwilliam (Frontend), @programjames (Map generation, Engine optimization), and @themmj (C++ kit, Engine optimization).

Citation

If you use the Lux AI Season 2 environment in your work, please cite this repository as so

@software{Lux_AI_Challenge_S1,
  author = {Tao, Stone and Doerschuk-Tiberi, Bovard},
  month = {10},
  title = {{Lux AI Challenge Season 2}},
  url = {https://github.com/Lux-AI-Challenge/Lux-Design-2022},
  version = {1.0.0},
  year = {2022}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

luxai2022-1.0.4.tar.gz (44.7 kB view details)

Uploaded Source

Built Distribution

luxai2022-1.0.4-py3-none-any.whl (52.3 kB view details)

Uploaded Python 3

File details

Details for the file luxai2022-1.0.4.tar.gz.

File metadata

  • Download URL: luxai2022-1.0.4.tar.gz
  • Upload date:
  • Size: 44.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.13

File hashes

Hashes for luxai2022-1.0.4.tar.gz
Algorithm Hash digest
SHA256 17df7f20e934ad4e4a3fffef860b3fa1ac9e5c3231a26a70fe486eeffb7bcaa2
MD5 b931e02741b91bcc15cf16ed8e78dde5
BLAKE2b-256 40cacbbd833c7dcf08aea8e9043c057cfd2842d9df23a0d7a086b570f717aa3f

See more details on using hashes here.

File details

Details for the file luxai2022-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: luxai2022-1.0.4-py3-none-any.whl
  • Upload date:
  • Size: 52.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.13

File hashes

Hashes for luxai2022-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 a5186dd310dab8bc1fa6624cfc7da82ecb966b0a6781f390d18cd862143919fa
MD5 ba187ee272c3478645e9a66a8a1f8e10
BLAKE2b-256 749f30773b39abc0f34dc1a86827526b28a86a758a50fd8d24a02ce1641e6a06

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page