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QDax is an open-source library with a streamlined and modular API for Quality-Diversity (QD) optimization algorithms in Jax.
Spea2: Improving the strength pareto evolutionary algorithm
Eckart Zitzler, Marco Laumanns, and Lothar Thiele · 2001
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A fast and elitist multiobjective genetic algorithm: Nsga-ii
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan · 2002
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SFERESv2: Evolvin’ in the multi-core world
J.-B. Mouret and S. Doncieux · 2010
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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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Illuminating search spaces by mapping elites
Jean-Baptiste Mouret and Jeff Clune · 2015
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Data-efficient exploration, optimization, and modeling of diverse designs through surrogate-assisted illumination
Adam Gaier, Alexander Asteroth, and Jean-Baptiste Mouret · 2017
Earlier work this paper cites.
Population based training of neural networks, 2017
Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M. Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, Chrisantha Fernando, and Koray Kavukcuoglu · 2017
Earlier work this paper cites.
Using centroidal voronoi tessellations to scale up the multidimensional archive of phenotypic elites algorithm
Vassilis Vassiliades, Konstantinos Chatzilygeroudis, and Jean-Baptiste Mouret · 2017
Earlier work this paper cites.
JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
Earlier work this paper cites.
Qdpy: A python framework for quality-diversity
L. Cazenille · 2018
Earlier work this paper cites.
Diversity is all you need: Learning skills without a reward function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine · 2018
Cited alongside, same era.
Empowering quality diversity in dungeon design with interactive constrained map-elites
Alberto Alvarez, Steve Dahlskog, Jose Font, and Julian Togelius · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Cited alongside, same era.
Scaling map-elites to deep neuroevolution
Cédric Colas, Vashisht Madhavan, Joost Huizinga, and Jeff Clune · 2020
Cited alongside, same era.
Covariance matrix adaptation for the rapid illumination of behavior space
Matthew C Fontaine, Julian Togelius, Stefanos Nikolaidis, and Amy K Hoover · 2020
Policy gradient assisted map-elites
Olle Nilsson and Antoine Cully · 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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Jumanji: Industry-driven hardware-accelerated rl environments, 2022
Clément Bonnet, Donal Byrne, Victor Le, Laurence Midgley, Daniel Luo, Cemlyn Waters, Sasha Abramowitz, Edan Toledo, Cyprien Courtot, Matthew Morris, Daniel Furelos-Blanco, Nathan Grinsztajn, Thomas D. Barrett, and Alexandre Laterre · 2022
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Benchmarking quality-diversity algorithms on neuroevolution for reinforcement learning, 2022
Manon Flageat, Bryan Lim, Luca Grillotti, Maxime Allard, Simón C. Smith, and Antoine Cully · 2022
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evosax: Jax-based evolution strategies, 2022
Robert Tjarko Lange · 2022
Later among the works it cites.
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Cited alongside, same era.
One solution is not all you need: Few-shot extrapolation via structured maxent rl
Saurabh Kumar, Aviral Kumar, Sergey Levine, and Chelsea Finn · 2020
Cited alongside, same era.
Dynamics-aware unsupervised discovery of skills
Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, and Karol Hausman · 2020
Cited alongside, same era.
Differentiable quality diversity
Matthew Fontaine and Stefanos Nikolaidis · 2021
Cited alongside, same era.
Brax - a differentiable physics engine for large scale rigid body simulation, 2021
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, and Olivier Bachem · 2021
Cited alongside, same era.
Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, et al · 2021
Cited alongside, same era.
Neuroevolution is a competitive alternative to reinforcement learning for skill discovery
Felix Chalumeau, Raphael Boige, Bryan Lim, Valentin Macé, Maxime Allard, Arthur Flajolet, Antoine Cully, and Thomas PIERROT
Cited in the paper.
Assessing quality-diversity neuro-evolution algorithms performance in hard exploration problems
Felix Chalumeau, Thomas Pierrot, Valentin Macé, Arthur Flajolet, Karim Beguir, Antoine Cully, and Nicolas Perrin-Gilbert
Cited in the paper.
Accelerated quality-diversity through massive parallelism
Bryan Lim, Maxime Allard, Luca Grillotti, and Antoine Cully · 2022
Later among the works it cites.
Evojax: Hardware-accelerated neuroevolution
Yujin Tang, Yingtao Tian, and David Ha · 2022
Later among the works it cites.
Empirical analysis of pga-map-elites for neuroevolution in uncertain domains
Manon Flageat, Felix Chalumeau, and Antoine Cully · 2023
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Evolving populations of diverse RL agents with MAP-elites
Thomas Pierrot and Arthur Flajolet · 2023
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