mlsanityData to 7 Oct 2026

Evolving Flying Machines in Minecraft Using Quality Diversity

arXiv 2302.00782 ↗First posted 1 Feb 2023cs.NE cs.AIcited by 4

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Abstract (arXiv)

Minecraft is a great testbed for human creativity that has inspired the design of various structures and even functioning machines, including flying machines. EvoCraft is an API for programmatically generating structures in Minecraft, but the initial work in this domain was not capable of evolving flying machines. This paper applies fitness-based evolution and quality diversity search in order to evolve flying machines. Although fitness alone can occasionally produce flying machines, thanks in part to a more sophisticated fitness function than was used previously, the quality diversity algorithm MAP-Elites is capable of discovering flying machines much more reliably, at least when an appropriate behavior characterization is used to guide the search for diverse solutions.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 14 of its 24 references that are in the map. First posted on arXiv 1 Feb 2023.

Builds on

14 of 24 references.

References · 14

  1. 2017Evolution Strategies as a Scalable Alternative to Reinforcement Learningcited by 555
  2. 2014Robots that can adapt like animalscited by 203
  3. 2019Covariance Matrix Adaptation for the Rapid Illumination of Behavior Spacecited by 78
  4. 2018Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Networkcited by 76
  5. 2020Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Networkcited by 51
  6. 2019Procedural Content Generation through Quality Diversitycited by 45
  7. 2016Super Mario as a String: Platformer Level Generation Via LSTMscited by 40
  8. 2021Growing 3D Artefacts and Functional Machines with Neural Cellular Automatacited by 38
  9. 2022Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learningcited by 37
  10. 2020EvoCraft: A New Challenge for Open-Endednesscited by 23
  11. 2020CPPN2GAN: Combining Compositional Pattern Producing Networks and GANs for Large-scale Pattern Generationcited by 19
  12. 2020Multi-Emitter MAP-Elites: Improving quality, diversity and convergence speed with heterogeneous sets of emitterscited by 14
2 more
  1. 2021World-GAN: a Generative Model for Minecraft Worldscited by 14
  2. 2022Open-Ended Evolution for Minecraft Building Generationcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.

  1. 2024DreamCraft: Text-Guided Generation of Functional 3D Environments in Minecraftcited by 17
  2. 2024Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essentialcited by 0
  3. 2025Expanding Horizons of Level Diversity via Multi-objective Evolutionary Learningcited by 0
  4. 2026Quality Diversity for Reliable Data Driven Time-Use Optimizationcited by 0