# Lode Encoder: AI-constrained co-creativity

arXiv: https://arxiv.org/abs/2308.01312 · HTML: https://mlsanity.com/paper/2308.01312/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 29 references that are in the map.
- First posted on arXiv 2 Aug 2023.

## Builds on (most cited first, 11 of 11)

- [Procedural Content Generation via Machine Learning (PCGML)](https://mlsanity.com/paper/1702.00539/) (2017)
- [The VGLC: The Video Game Level Corpus](https://mlsanity.com/paper/1606.07487/) (2016)
- [Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators](https://mlsanity.com/paper/1901.06417/) (2019)
- [Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencoder](https://mlsanity.com/paper/2102.12463/) (2021)
- [Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks](https://mlsanity.com/paper/2004.00151/) (2020)
- [Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites](https://mlsanity.com/paper/1906.05175/) (2019)
- [Conditional Level Generation and Game Blending](https://mlsanity.com/paper/2010.07735/) (2020)
- [Deep Interactive Evolution](https://mlsanity.com/paper/1801.08230/) (2018)
- [Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial Networks](https://mlsanity.com/paper/2101.07868/) (2021)
- [Towards Game Design via Creative Machine Learning (GDCML)](https://mlsanity.com/paper/2008.13548/) (2020)
- [Multi-Domain Level Generation and Blending with Sketches via Example-Driven BSP and Variational Autoencoders](https://mlsanity.com/paper/2006.09807/) (2020)

## Built on by (most cited first, 6 of 6)

- [The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game Designer](https://mlsanity.com/paper/2403.02454/) (2024)
- [A Systematic Review of Human-AI Co-Creativity](https://mlsanity.com/paper/2506.21333/) (2025)
- [Mechanic Maker: Accessible Game Development Via Symbolic Learning Program Synthesis](https://mlsanity.com/paper/2410.01096/) (2024)
- [A Controllable Co-Creative Agent for Game System Design](https://mlsanity.com/paper/2308.02317/) (2023)
- [Lode Enhancer: Level Co-creation Through Scaling](https://mlsanity.com/paper/2308.01543/) (2023)
- [Evolutionary Level Repair](https://mlsanity.com/paper/2506.19359/) (2025)

## Abstract (arXiv)

We present Lode Encoder, a gamified mixed-initiative level creation system for the classic platform-puzzle game Lode Runner. The system is built around several autoencoders which are trained on sets of Lode Runner levels. When fed with the user's design, each autoencoder produces a version of that design which is closer in style to the levels that it was trained on. The Lode Encoder interface allows the user to build and edit levels through 'painting' from the suggestions provided by the autoencoders. Crucially, in order to encourage designers to explore new possibilities, the system does not include more traditional editing tools. We report on the system design and training procedure, as well as on the evolution of the system itself and user tests.