mlsanityData to 14 Oct 2026

Co-Creative Level Design via Machine Learning

arXiv 1809.09420 ↗First posted 25 Sep 2018cs.AI cs.LGcited by 18

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Abstract (arXiv)

Procedural Level Generation via Machine Learning (PLGML), the study of generating game levels with machine learning, has received a large amount of recent academic attention. For certain measures these approaches have shown success at replicating the quality of existing game levels. However, it is unclear the extent to which they might benefit human designers. In this paper we present a framework for co-creative level design with a PLGML agent. In support of this framework we present results from a user study and results from a comparative study of PLGML approaches.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Sep 2018.

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Citing papers per year: 2021: 7; 2022: 4; 2023: 1; 2024: 2; 2025: 3; 2026: 1.

18 papers.

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  1. 2021Plug-and-Blend: A Framework for Controllable Story Generation with Blended Control Codescited by 19
  2. 2022Learning Controllable 3D Level Generatorscited by 19
  3. 2022CLIP meets GamePhysics: Towards bug identification in gameplay videos using zero-shot transfer learningcited by 15
  4. 2021TaikoNation: Patterning-focused Chart Generation for Rhythm Action Gamescited by 9
  5. 2022Mutation Models: Learning to Generate Levels by Imitating Evolutioncited by 9
  6. 2024PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generatorscited by 7
  7. 2021Arachnophobia Exposure Therapy using Experience-driven Procedural Content Generation via Reinforcement Learning (EDPCGRL)cited by 5
  8. 2025A Systematic Review of Human-AI Co-Creativitycited by 4
  9. 2021Generating Lode Runner Levels by Learning Player Paths with LSTMscited by 3
  10. 2023Procedural Content Generation via Knowledge Transformation (PCG-KT)cited by 2
  11. 2021Toward Co-creative Dungeon Generation via Transfer Learningcited by 1
  12. 2021The Impact of Visualizing Design Gradients for Human Designerscited by 1
6 more
  1. 2022Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systemscited by 1
  2. 2025Video Game Level Design as a Multi-Agent Reinforcement Learning Problemcited by 1
  3. 2021Advances in Electron Microscopy with Deep Learningcited by 0
  4. 2024Beyond Following: Mixing Active Initiative into Computational Creativitycited by 0
  5. 2025Text-to-Level Diffusion Models With Various Text Encoders for Super Mario Broscited by 0
  6. 2026Representing and Generating Levels Over Time through Playtrace Reconstructive Partitioningcited by 0