mlsanityData to 14 Oct 2026

Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials

arXiv 2204.05217 ↗First posted 11 Apr 2022cs.AIcited by 1

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Abstract (arXiv)

In this paper, we present a method for automated persona-driven video game tutorial level generation. Tutorial levels are scenarios in which the player can explore and discover different rules and game mechanics. Procedural personas can guide generators to create content which encourages or discourages certain playstyle behaviors. In this system, we use procedural personas to calculate the behavioral characteristics of levels which are evolved using the quality-diversity algorithm known as Constrained MAP-Elites. An evolved map's quality is determined by its simplicity: the simpler it is, the better it is. Within this work, we show that the generated maps can strongly encourage or discourage different persona-like behaviors and range from simple solutions to complex puzzle-levels, making them perfect candidates for a tutorial generative system.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 50 references that are in the map. First posted on arXiv 11 Apr 2022.

Builds on

17 of 50 references.

References · 17

  1. 2015Illuminating search spaces by mapping elitescited by 425
  2. 2019Procedural Content Generation through Quality Diversitycited by 45
  3. 2019Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundariescited by 32
  4. 2018Automated Playtesting with Procedural Personas through MCTS with Evolved Heuristicscited by 28
  5. 2018Talakat: Bullet Hell Generation through Constrained Map-Elitescited by 26
  6. 2021Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuildingcited by 26
  7. 2021Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Studycited by 25
  8. 2019Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elitescited by 18
  9. 2020Mech-Elites: Illuminating the Mechanic Space of GVGAIcited by 13
  10. 2018Generating Levels That Teach Mechanicscited by 9
  11. 2019Intentional Computational Level Designcited by 9
  12. 2020Mario Level Generation From Mechanics Using Scene Stitchingcited by 8
5 more
  1. 2020Say "Sul Sul!" to SimSim, A Sims-Inspired Platform for Sandbox Game AIcited by 5
  2. 2021Arachnophobia Exposure Therapy using Experience-driven Procedural Content Generation via Reinforcement Learning (EDPCGRL)cited by 5
  3. 2018AtDelfi: Automatically Designing Legible, Full Instructions For Gamescited by 4
  4. 2021Dynamic Difficulty Adjustment in Virtual Reality Exergames through Experience-driven Procedural Content Generationcited by 3
  5. 2022Predicting Personas Using Mechanic Frequencies and Game State Tracescited by 2

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Cited by year

Citing papers per year: 2023: 1.

1 paper.

  1. 2023The Quest for Content: A Survey of Search-Based Procedural Content Generation for Video Gamescited by 0