mlsanityData to 7 Oct 2026

Game Mechanic Alignment Theory and Discovery

arXiv 2102.10247 ↗First posted 20 Feb 2021cs.AIcited by 1

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Abstract (arXiv)

We present a new concept called Game Mechanic Alignment theory as a way to organize game mechanics through the lens of systemic rewards and agential motivations. By disentangling player and systemic influences, mechanics may be better identified for use in an automated tutorial generation system, which could tailor tutorials for a particular playstyle or player. Within, we apply this theory to several well-known games to demonstrate how designers can benefit from it, we describe a methodology for how to estimate "mechanic alignment", and we apply this methodology on multiple games in the GVGAI framework. We discuss how effectively this estimation captures agential motivations and systemic rewards and how our theory could be used as an alternative way to find mechanics for tutorial generation.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 58 references that are in the map. First posted on arXiv 20 Feb 2021.

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13 of 58 references.

References · 13

  1. 2018General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithmscited by 45
  2. 2018Automated Playtesting with Procedural Personas through MCTS with Evolved Heuristicscited by 28
  3. 2018Deep Reinforcement Learning for General Video Game AIcited by 25
  4. 2019General Video Game Rule Generationcited by 17
  5. 2020Mech-Elites: Illuminating the Mechanic Space of GVGAIcited by 13
  6. 2018Generating Levels That Teach Mechanicscited by 9
  7. 2019Intentional Computational Level Designcited by 9
  8. 2020Mario Level Generation From Mechanics Using Scene Stitchingcited by 8
  9. 2018Deceptive Gamescited by 5
  10. 2018AtDelfi: Automatically Designing Legible, Full Instructions For Gamescited by 4
  11. 2017Automatic Mapping of NES Games with Mappycited by 3
  12. 2018"Press Space to Fire": Automatic Video Game Tutorial Generationcited by 3
1 more
  1. 2017Deriving Quests from Open World Mechanicscited by 1

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Citing papers per year: 2022: 1.

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