mlsanityData to 7 Oct 2026

Measuring Diversity of Game Scenarios

arXiv 2404.15192 ↗First posted 15 Apr 2024cs.AIcited by 5

Not on the map. Why?

Abstract (arXiv)

This survey comprehensively reviews the multi-dimensionality of game scenario diversity, spotlighting the innovative use of procedural content generation and other fields as cornerstones for enriching player experiences through diverse game scenarios. By traversing a wide array of disciplines, from affective modeling and multi-agent systems to psychological studies, our research underscores the importance of diverse game scenarios in gameplay and education. Through a taxonomy of diversity metrics and evaluation methods, we aim to bridge the current gaps in literature and practice, offering insights into effective strategies for measuring and integrating diversity in game scenarios. Our analysis highlights the necessity for a unified taxonomy to aid developers and researchers in crafting more engaging and varied game worlds. This survey not only charts a path for future research in diverse game scenarios but also serves as a handbook for industry practitioners seeking to leverage diversity as a key component of game design and development.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 64 of its 237 references that are in the map. First posted on arXiv 15 Apr 2024.

Builds on

64 of 237 references.

References · 64

  1. 2018Diversity is All You Need: Learning Skills without a Reward Functioncited by 734
  2. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 136
  3. 2017Stochastic Neural Networks for Hierarchical Reinforcement Learningcited by 124
  4. 2024Large Language Models and Games: A Survey and Roadmapcited by 91
  5. 2019Covariance Matrix Adaptation for the Rapid Illumination of Behavior Spacecited by 78
  6. 2018Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Networkcited by 76
  7. 2020Deep Learning for Procedural Content Generationcited by 73
  8. 2023Level Generation Through Large Language Modelscited by 68
  9. 2023MarioGPT: Open-Ended Text2Level Generation through Large Language Modelscited by 63
  10. 2019Increasing Generality in Machine Learning through Procedural Content Generationcited by 58
  11. 2020Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Networkcited by 51
  12. 2019Procedural Content Generation through Quality Diversitycited by 45
38 more
  1. 2016Super Mario as a String: Platformer Level Generation Via LSTMscited by 40
  2. 2021Learning Controllable Content Generatorscited by 40
  3. 2019Bootstrapping Conditional GANs for Video Game Level Generationcited by 35
  4. 2021Illuminating Diverse Neural Cellular Automata for Level Generationcited by 35
  5. 2019Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundariescited by 32
  6. 2021Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencodercited by 27
  7. 2018Talakat: Bullet Hell Generation through Constrained Map-Elitescited by 26
  8. 2021Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuildingcited by 26
  9. 2021Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Studycited by 25
  10. 2020Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networkscited by 22
  11. 2020Baba is Y'all: Collaborative Mixed-Initiative Level Designcited by 20
  12. 2022Learning Controllable 3D Level Generatorscited by 19
  13. 2019Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elitescited by 18
  14. 2021The Arousal video Game AnnotatIoN (AGAIN) Datasetcited by 18
  15. 2019General Video Game Rule Generationcited by 17
  16. 2019Diverse Agents for Ad-Hoc Cooperation in Hanabicited by 17
  17. 2019Tile Pattern KL-Divergence for Analysing and Evolving Game Levelscited by 16
  18. 2018DOOM Level Generation using Generative Adversarial Networkscited by 15
  19. 2021Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial Networkscited by 14
  20. 2021World-GAN: a Generative Model for Minecraft Worldscited by 14
  21. 2022Path of Destruction: Learning an Iterative Level Generator Using a Small Datasetcited by 14
  22. 2023Games for Artificial Intelligence Research: A Review and Perspectivescited by 14
  23. 2020Mech-Elites: Illuminating the Mechanic Space of GVGAIcited by 13
  24. 2018Quality Diversity Through Surprisecited by 12
  25. 2020Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature Dimensionscited by 11
  26. 2023Affective Game Computing: A Surveycited by 11
  27. 2021Monte Carlo Elites: Quality-Diversity Selection as a Multi-Armed Bandit Problemcited by 10
  28. 2019Novelty Search for Deep Reinforcement Learning Policy Network Weights by Action Sequence Edit Metric Distancecited by 9
  29. 2019Intentional Computational Level Designcited by 9
  30. 2022Open-Ended Evolution for Minecraft Building Generationcited by 9
  31. 2020Multi-Objective level generator generation with Marahelcited by 8
  32. 2022Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game Levelscited by 8
  33. 2021Detecting and Adapting to Novelty in Gamescited by 7
  34. 202110 Years of the PCG workshop: Past and Future Trendscited by 6
  35. 2023The Right Variety: Improving Expressive Range Analysis with Metric Selection Methodscited by 6
  36. 2021Comparing PCG metrics with Human Evaluation in Minecraft Settlement Generationcited by 5
  37. 2021Hybrid Encoding For Generating Large Scale Game Level Patterns With Local Variationscited by 4
  38. 2021Generating Lode Runner Levels by Learning Player Paths with LSTMscited by 3

50 most cited of 64 All 64 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Gamescited by 8
  2. 2025Word2Minecraft: Generating 3D Game Levels through Large Language Modelscited by 3
  3. 2025Diverse Planning with Simulators via Linear Temporal Logiccited by 1
  4. 2025Expanding Horizons of Level Diversity via Multi-objective Evolutionary Learningcited by 0
  5. 2026From Stories to Cities to Games: A Qualitative Evaluation of Behaviour Planningcited by 0