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Generative Adversarial Networks (GANs) are a machine learning approach capable of generating novel example outputs across a space of provided training examples.
A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II
Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. 2002 · 2002
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Texturing and Modeling: A Procedural Approach
David S. Ebert, F. Kenton Musgrave, Darwyn Peachey, Ken Perlin, and Steven Worley. 2002 · 2002
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Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES)
Nikolaus Hansen, Sibylle D Müller, and Petros Koumoutsakos. 2003 · 2003
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The 2010 Mario AI championship: Level Generation Track
Noor Shaker, Julian Togelius, Georgios N Yannakakis, and others. 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. 2011b · 2011
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Brian G Woolley and Kenneth O Stanley. 2011 · 2011
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Evolving Levels for Super Mario Bros Using Grammatical Evolution. In Computational Intelligence and Games (CIG), 2012 IEEE Conference on
Noor Shaker, Miguel Nicolau, Georgios N Yannakakis, Julian Togelius, and Michael O’neill. 2012 · 2012
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Mazes in Videogames: meaning, metaphor and design
Alison Gazzard. 2013 · 2013
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The Mario AI Championship 2009-2012
Julian Togelius, Noor Shaker, Sergey Karakovskiy, and Georgios N. Yannakakis. 2013b · 2013
Cited alongside, same era.
Generative Adversarial Nets. In Advances in Neural Information Processing Systems
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, and others. 2014 · 2014
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Rishabh Jain, Aaron Isaksen, Christoffer Holmgård, and Julian Togelius. 2016 · 2016
Cited alongside, same era.
General Video Game Level Generation. In Proceedings of the Genetic and Evolutionary Computation Conference 2016
Ahmed Khalifa, Diego Perez-Liebana, Simon M Lucas, and Julian Togelius. 2016 · 2016
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Matt J Kusner and José Miguel Hernández-Lobato. 2016 · 2016
Procedural Content Generation in Games
Noor Shaker, Julian Togelius, and Mark J Nelson. 2016 · 2016
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Super Mario as a String: Platformer Level Generation via LSTMs. In 1st International Joint Conference of DiGRA and FDG
Adam Summerville and Michael Mateas. 2016 · 2016
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The VGLC: The Video Game Level Corpus
Adam James Summerville, Sam Snodgrass, Michael Mateas, and Santiago Ontañón Villar. 2016 · 2016
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Wasserstein Generative Adversarial Networks. In Proceedings of the 34nd International Conference on Machine Learning, ICML
Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
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DeepMasterPrint: Generating Fingerprints for Presentation Attacks
Philip Bontrager, Julian Togelius, and Nasir Memon. 2017 · 2017
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Cited alongside, same era.
Adversarial Autoencoders. In International Conference on Learning Representations
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow. 2016 · 2016
Cited alongside, same era.
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
Anh Nguyen, Jason Yosinski, Yoshua Bengio, Alexey Dosovitskiy, and Jeff Clune. 2016 · 2016
Cited alongside, same era.
Alec Radford, Luke Metz, and Soumith Chintala. 2016 · 2016
Cited alongside, same era.
Procedural content generation: Goals, challenges and actionable steps. In Dagstuhl Follow-Ups
Julian Togelius, Alex J Champandard, Pier Luca Lanzi, and others. 2013a
Cited in the paper.
What is procedural content generation? Mario on the borderline. In Proceedings of the 2nd International Workshop on Procedural Content Generation in Games
Julian Togelius, Emil Kastbjerg, David Schedl, and Georgios N Yannakakis. 2011a
Cited in the paper.
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville. 2017 · 2017
Later among the works it cites.
Procedural Content Generation via Machine Learning (PCGML)
Adam Summerville, Sam Snodgrass, Matthew Guzdial, and others. 2017 · 2017
Later among the works it cites.
Deep Interactive Evolution
Philip Bontrager, Wending Lin, Julian Togelius, and Sebastian Risi. 2018 · 2018
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