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Quality diversity (QD) is a growing branch of stochastic optimization research that studies the problem of generating an archive of solutions that maximize a given objective function but are also diverse with respect to a set of specified measure functions.
On the shortest arborescence of a directed graph
Yoeng-Jin Chu · 1965
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Continuous univariate distributions, volume 2 , volume 289
Norman L Johnson, Samuel Kotz, and Narayanaswamy Balakrishnan · 1995
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Bidirectional relation between cma evolution strategies and natural evolution strategies
Youhei Akimoto, Yuichi Nagata, Isao Ono, and Shigenobu Kobayashi · 2010
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Comparing results of 31 algorithms from the black-box optimization benchmarking bbob-2009
Nikolaus Hansen, Anne Auger, Raymond Ros, Steffen Finck, and Petr Pošík · 2010
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Stochastic gradient descent tricks
Léon Bottou · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Robots that can adapt like animals
Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Illuminating search spaces by mapping elites
Jean-Baptiste Mouret and Jeff Clune · 2015
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Confronting the challenge of quality diversity
Justin K Pugh, Lisa B Soros, Paul A Szerlip, and Kenneth O Stanley · 2015
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Coco: A platform for comparing continuous optimizers in a black-box setting
N. Hansen, A. Auger, O. Mersmann, T. Tusar, and D. Brockhoff · 2016
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The cma evolution strategy: A tutorial
Nikolaus Hansen · 2016
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Quality diversity: A new frontier for evolutionary computation
Justin K Pugh, Lisa B Soros, and Kenneth O Stanley · 2016
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Rapid phenotypic landscape exploration through hierarchical spatial partitioning
Davy Smith, Laurissa Tokarchuk, and Geraint Wiggins · 2016
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Tom White · 2016
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Optimizing the latent space of generative networks
Piotr Bojanowski, Armand Joulin, David Lopez-Paz, and Arthur Szlam · 2017
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Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth O Stanley, and Jeff Clune · 2017
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Quality and diversity optimization: A unifying modular framework
Antoine Cully and Yiannis Demiris · 2017
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A mathematical introduction to robotic manipulation
Richard M Murray, Zexiang Li, and S Shankar Sastry · 2017
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Deep feature interpolation for image content changes
Paul Upchurch, Jacob Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala, and Kilian Weinberger · 2017
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Using centroidal voronoi tessellations to scale up the multidimensional archive of phenotypic elites algorithm
Vassilis Vassiliades, Konstantinos Chatzilygeroudis, and Jean-Baptiste Mouret · 2017
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Deepmasterprints: Generating masterprints for dictionary attacks via latent variable evolution
Philip Bontrager, Aditi Roy, Julian Togelius, Nasir Memon, and Arun Ross · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Data-efficient design exploration through surrogate-assisted illumination
Adam Gaier, Alexander Asteroth, and Jean-Baptiste Mouret · 2018
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Deepfake video detection using recurrent neural networks
David Güera and Edward J Delp · 2018
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Dynamic mutation in map-elites for robotic repertoire generation
Jørgen Nordmoen, Eivind Samuelsen, Kai Olav Ellefsen, and Kyrre Glette · 2018
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Discovering the elite hypervolume by leveraging interspecies correlation
Bop-elites, a bayesian optimisation algorithm for quality-diversity search
Paul Kent and Juergen Branke · 2020
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Pulse: Self-supervised photo upsampling via latent space exploration of generative models
Sachit Menon, Alexandru Damian, Shijia Hu, Nikhil Ravi, and Cynthia Rudin · 2020
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Effective diversity in population-based reinforcement learning
Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, and Stephen Roberts · 2020
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Cppn2gan: Combining compositional pattern producing networks and gans for large-scale pattern generation
Jacob Schrum, Vanessa Volz, and Sebastian Risi · 2020
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Quality-diversity optimization: a novel branch of stochastic optimization
Konstantinos Chatzilygeroudis, Antoine Cully, Vassilis Vassiliades, and Jean-Baptiste Mouret · 2021
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Vassilis Vassiliades and Jean-Baptiste Mouret · 2018
Cited alongside, same era.
Evolving mario levels in the latent space of a deep convolutional generative adversarial network
Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M Lucas, Adam Smith, and Sebastian Risi · 2018
Cited alongside, same era.
Alphastar: An evolutionary computation perspective
Kai Arulkumaran, Antoine Cully, and Julian Togelius · 2019
Cited alongside, same era.
Mapping hearthstone deck spaces through map-elites with sliding boundaries
Matthew C Fontaine, Scott Lee, Lisa B Soros, Fernando de Mesentier Silva, Julian Togelius, and Amy K Hoover · 2019
Cited alongside, same era.
Procedural content generation through quality diversity
Daniele Gravina, Ahmed Khalifa, Antonios Liapis, Julian Togelius, and Georgios N Yannakakis · 2019
Cited alongside, same era.
CMA-ES/pycma on Github
Nikolaus Hansen, Youhei Akimoto, and Petr Baudis · 2019
Cited alongside, same era.
On the" steerability" of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2019
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First return, then explore
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O Stanley, and Jeff Clune · 2021
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A quality diversity approach to automatically generating human-robot interaction scenarios in shared autonomy
Matthew Fontaine and Stefanos Nikolaidis · 2021
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Clipdraw: Exploring text-to-drawing synthesis through language-image encoders
Kevin Frans, LB Soros, and Olaf Witkowski · 2021
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Generating images from caption and vice versa via clip-guided generative latent space search
Federico A Galatolo, Mario GCA Cimino, and Gigliola Vaglini · 2021
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The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning
Suyun Liu and Luis Nunes Vicente · 2021
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Policy gradient assisted map-elites
Olle Nilsson and Antoine Cully · 2021
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Generating images from prompts using clip and stylegan, 2021
Victor Perez · 2021
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Learning transferable visual models from natural language supervision
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Policy manifold search: Exploring the manifold hypothesis for diversity-based neuroevolution
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Efficient multi-objective optimization for deep learning
Michael Ruchte and Josif Grabocka · 2021
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Anurag Sarkar and Seth Cooper · 2021
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Monte carlo elites: Quality-diversity selection as a multi-armed bandit problem
Konstantinos Sfikas, Antonios Liapis, and Georgios N. Yannakakis · 2021
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Illuminating the space of beatable lode runner levels produced by various generative adversarial networks
Kirby Steckel and Jacob Schrum · 2021
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pyribs: A bare-bones python library for quality diversity optimization
Bryon Tjanaka, Matthew C. Fontaine, Yulun Zhang, Sam Sommerer, Nathan Dennler, and Stefanos Nikolaidis · 2021
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Illuminating the latent space of an mnist gan
Yulun Zhang, Bryon Tjanaka, Matthew C. Fontaine, and Stefanos Nikolaidis · 2021
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