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Procedural Content Generation via Reinforcement Learning (PCGRL) foregoes the need for large human-authored data-sets and allows agents to train explicitly on functional constraints, using computable, user-defined measures of quality instead of target output.
Evolutionary game design
Cameron Browne and Frederic Maire. 2010 · 2010
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Search-based procedural generation of maze-like levels
Daniel Ashlock, Colin Lee, and Cameron McGuinness. 2011 · 2011
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Search-based procedural content generation: A taxonomy and survey
Julian Togelius, Georgios N Yannakakis, Kenneth O Stanley, and Cameron Browne. 2011 · 2011
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A procedural procedural level generator generator. In 2012 IEEE Conference on Computational Intelligence and Games (CIG) . IEEE, 335–341
Manuel Kerssemakers, Jeppe Tuxen, Julian Togelius, and Georgios N Yannakakis. 2012 · 2012
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Evolving playable content for cut the rope through a simulation-based approach. In Ninth Artificial Intelligence and Interactive Digital Entertainment Conference
Noor Shaker, Mohammad Shaker, and Julian Togelius. 2013 · 2013
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Linear levels through n-grams. In Proceedings of the 18th International Academic MindTrek Conference: Media Business, Management, Content & Services . 200–206
Steve Dahlskog, Julian Togelius, and Mark J Nelson. 2014 · 2014
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Automatic puzzle level generation: A general approach using a description language. Institute of Electrical and Electronics Engineers
Ahmed Khalifa and Magda Fayek. 2015 · 2015
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Markov by candlelight
Jason Grinblat. 2016 · 2016
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Autoencoders for level generation, repair, and recognition. In Proceedings of the ICCC workshop on computational creativity and games , Vol. 9
Rishabh Jain, Aaron Isaksen, Christoffer Holmgård, and Julian Togelius. 2016 · 2016
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General video game ai: Competition, challenges and opportunities. In AAAI Conference on Artificial Intelligence
Diego Perez-Liebana, Spyridon Samothrakis, Julian Togelius, Tom Schaul, and Simon M Lucas. 2016 · 2016
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Procedural content generation in games
Noor Shaker, Julian Togelius, and Mark J Nelson. 2016 · 2016
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Learning to generate video game maps using markov models
Sam Snodgrass and Santiago Ontanón. 2016 · 2016
Cited alongside, same era.
Learning player tailored content from observation: Platformer level generation from video traces using lstms. In Twelfth artificial intelligence and interactive digital entertainment conference
Adam Summerville, Matthew Guzdial, Michael Mateas, and Mark O Riedl. 2016 · 2016
Cited alongside, same era.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Cited alongside, same era.
Q-deckrec: A fast deck recommendation system for collectible card games. In 2018 IEEE conference on Computational Intelligence and Games (CIG) . IEEE, 1–8
Zhengxing Chen, Christopher Amato, Truong-Huy D Nguyen, Seth Cooper, Yizhou Sun, and Magy Seif El-Nasr. 2018 · 2018
Cited alongside, same era.
Pcgrl: Procedural content generation via reinforcement learning. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment , Vol. 16. 95–101
Ahmed Khalifa, Philip Bontrager, Sam Earle, and Julian Togelius. 2020 · 2020
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Multi-Objective level generator generation with Marahel. In International Conference on the Foundations of Digital Games . 1–8
Ahmed Khalifa and Julian Togelius. 2020 · 2020
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Bootstrapping conditional gans for video game level generation. In 2020 IEEE Conference on Games (CoG) . IEEE, 41–48
Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green, Niels Justesen, Sebastian Risi, and Julian Togelius. 2020 · 2020
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Learning to Generate Levels From Nothing. In 2021 IEEE Conference on Games (CoG) . IEEE, 1–8
Philip Bontrager and Julian Togelius. 2021 · 2021
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Mixed-initiative level design with rl brush. In International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar) . Springer, 412–426
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Matthew Guzdial, Nicholas Liao, and Mark Riedl. 2018 · 2018
Cited alongside, same era.
Procedural content generation via machine learning (PCGML)
Adam Summerville, Sam Snodgrass, Matthew Guzdial, Christoffer Holmgård, Amy K Hoover, Aaron Isaksen, Andy Nealen, and Julian Togelius. 2018 · 2018
Cited alongside, same era.
Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M Lucas, Adam Smith, and Sebastian Risi. 2018 · 2018
Cited alongside, same era.
Mapping hearthstone deck spaces through map-elites with sliding boundaries. In Proceedings of The Genetic and Evolutionary Computation Conference . 161–169
Matthew C Fontaine, Scott Lee, Lisa B Soros, Fernando de Mesentier Silva, Julian Togelius, and Amy K Hoover. 2019 · 2019
Cited alongside, same era.
Tree search versus optimization approaches for map generation. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment , Vol. 16. 24–30
Debosmita Bhaumik, Ahmed Khalifa, Michael Green, and Julian Togelius. 2020 · 2020
Cited alongside, same era.
Emergent complexity and zero-shot transfer via unsupervised environment design
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, and Sergey Levine. 2020 · 2020
Cited alongside, same era.
Covariance matrix adaptation for the rapid illumination of behavior space. In Proceedings of the 2020 genetic and evolutionary computation conference . 94–102
Matthew C Fontaine, Julian Togelius, Stefanos Nikolaidis, and Amy K Hoover. 2020 · 2020
Cited alongside, same era.
Omar Delarosa, Hang Dong, Mindy Ruan, Ahmed Khalifa, and Julian Togelius. 2021 · 2021
Later among the works it cites.
Learning controllable content generators. In 2021 IEEE Conference on Games (CoG) . IEEE, 1–9
Sam Earle, Maria Edwards, Ahmed Khalifa, Philip Bontrager, and Julian Togelius. 2021a · 2021
Later among the works it cites.
Illuminating Diverse Neural Cellular Automata for Level Generation
Sam Earle, Justin Snider, Matthew C Fontaine, Stefanos Nikolaidis, and Julian Togelius. 2021b · 2021
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EvoCraft: A new challenge for open-endedness. In International Conference on the Applications of Evolutionary Computation (Part of EvoStar) . Springer, 325–340
Djordje Grbic, Rasmus Berg Palm, Elias Najarro, Claire Glanois, and Sebastian Risi. 2021 · 2021
Later among the works it cites.
Replay-guided adversarial environment design
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, and Tim Rocktäschel. 2021 · 2021
Later among the works it cites.
Arachnophobia exposure therapy using experience-driven procedural content generation via reinforcement learning (EDPCGRL). In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment , Vol. 17. 164–171
Athar Mahmoudi-Nejad, Matthew Guzdial, and Pierre Boulanger. 2021 · 2021
Later among the works it cites.
Evolving Curricula with Regret-Based Environment Design
Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob Foerster, Edward Grefenstette, and Tim Rocktäschel. 2022 · 2022
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