mlsanityData to 14 Oct 2026

Lode Encoder: AI-constrained co-creativity

arXiv 2308.01312 ↗First posted 2 Aug 2023cs.LG cs.AIcited by 6

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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.

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

11 of 29 references.

References · 11

  1. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 137
  2. 2016The VGLC: The Video Game Level Corpuscited by 41
  3. 2019Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creatorscited by 31
  4. 2021Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencodercited by 27
  5. 2020Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networkscited by 22
  6. 2019Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elitescited by 18
  7. 2020Conditional Level Generation and Game Blendingcited by 17
  8. 2018Deep Interactive Evolutioncited by 14
  9. 2021Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial Networkscited by 14
  10. 2020Towards Game Design via Creative Machine Learning (GDCML)cited by 13
  11. 2020Multi-Domain Level Generation and Blending with Sketches via Example-Driven BSP and Variational Autoencoderscited by 11

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 2; 2025: 2.

6 papers.

  1. 2024The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game Designercited by 12
  2. 2025A Systematic Review of Human-AI Co-Creativitycited by 4
  3. 2024Mechanic Maker: Accessible Game Development Via Symbolic Learning Program Synthesiscited by 3
  4. 2023A Controllable Co-Creative Agent for Game System Designcited by 2
  5. 2023Lode Enhancer: Level Co-creation Through Scalingcited by 1
  6. 2025Evolutionary Level Repaircited by 0