Mutation Models: Learning to Generate Levels by Imitating Evolution-Reference-Cited by-同舟云学术

Mutation Models: Learning to Generate Levels by Imitating Evolution

Published:2022-09-05 Issue: Volume: Page:
ISSN:
Container-title:FDG '22: Proceedings of the 17th International Conference on the Foundations of Digital Games
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Author:

Khalifa Ahmed¹,Togelius Julian²,Green Michael Cerny²

Affiliation:

1. Insitute of Digital Games, University of Malta, Malta

2. Game Innovation Lab, New York University, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3555858.3563267

Reference46 articles.

1. Kamal Abboud and Marc Schoenauer . 2001 . Surrogate deterministic mutation: Preliminary results . In International Conference on Artificial Evolution. Springer, 104–116 . Kamal Abboud and Marc Schoenauer. 2001. Surrogate deterministic mutation: Preliminary results. In International Conference on Artificial Evolution. Springer, 104–116.

2. Daniel Ashlock . 2010 . Automatic generation of game elements via evolution . In Conference on Computational Intelligence and Games. IEEE, 289–296 . Daniel Ashlock. 2010. Automatic generation of game elements via evolution. In Conference on Computational Intelligence and Games. IEEE, 289–296.

3. Search-Based Procedural Generation of Maze-Like Levels

4. Hans-Georg Beyer and Hans-Paul Schwefel . 2002. Evolution strategies–a comprehensive introduction. Natural computing 1, 1 ( 2002 ), 3–52. Hans-Georg Beyer and Hans-Paul Schwefel. 2002. Evolution strategies–a comprehensive introduction. Natural computing 1, 1 (2002), 3–52.

5. Debosmita Bhaumik Ahmed Khalifa Michael Green and Julian Togelius. 2020. Tree search versus optimization approaches for map generation. In Artificial Intelligence and Interactive Digital Entertainment Vol. 16. AAAI 24–30. Debosmita Bhaumik Ahmed Khalifa Michael Green and Julian Togelius. 2020. Tree search versus optimization approaches for map generation. In Artificial Intelligence and Interactive Digital Entertainment Vol. 16. AAAI 24–30.

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