# Keke AI Competition: Solving puzzle levels in a dynamically changing mechanic space

arXiv: https://arxiv.org/abs/2209.04911 · HTML: https://mlsanity.com/paper/2209.04911/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 22 references that are in the map.
- First posted on arXiv 11 Sep 2022.

## Builds on (most cited first, 7 of 7)

- [The NetHack Learning Environment](https://mlsanity.com/paper/2006.13760/) (2020)
- [Baba is Y'all: Collaborative Mixed-Initiative Level Design](https://mlsanity.com/paper/2003.14294/) (2020)
- [A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances](https://mlsanity.com/paper/2110.00898/) (2021)
- [Multi-Objective level generator generation with Marahel](https://mlsanity.com/paper/2005.08368/) (2020)
- [Evolving Agents for the Hanabi 2018 CIG Competition](https://mlsanity.com/paper/1809.09764/) (2018)
- [Solving Sokoban with forward-backward reinforcement learning](https://mlsanity.com/paper/2105.01904/) (2021)
- [Baba is Y'all 2.0: Design and Investigation of a Collaborative Mixed-Initiative System](https://mlsanity.com/paper/2203.02035/) (2022)

## Built on by (most cited first, 1 of 1)

- [From Code to Play: Benchmarking Program Search for Games Using Large Language Models](https://mlsanity.com/paper/2412.04057/) (2024)

## Abstract (arXiv)

The Keke AI Competition introduces an artificial agent competition for the game Baba is You - a Sokoban-like puzzle game where players can create rules that influence the mechanics of the game. Altering a rule can cause temporary or permanent effects for the rest of the level that could be part of the solution space. The nature of these dynamic rules and the deterministic aspect of the game creates a challenge for AI to adapt to a variety of mechanic combinations in order to solve a level. This paper describes the framework and evaluation metrics used to rank submitted agents and baseline results from sample tree search agents.