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Quality-Diversity algorithms, such as MAP-Elites, are a branch of Evolutionary Computation generating collections of diverse and high-performing solutions, that have been successfully applied to a variety of domains and particularly in evolutionary robotics.
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Multilayer feedforward networks are universal approximators
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Scaling MAP-Elites to Deep Neuroevolution
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One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL
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Quality-Diversity Optimization: a novel branch of stochastic optimization
Konstantinos Chatzilygeroudis, Antoine Cully, Vassilis Vassiliades, and Jean-Baptiste Mouret. 2020 · 2012
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Playing Atari with Deep Reinforcement Learning
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Robots that can adapt like animals
Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret. 2015 · 2015
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Human-level control through deep reinforcement learning
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Illuminating search spaces by mapping elites
Jean-Baptiste Mouret and Jeff Clune. 2015 · 2015
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Universal Value Function Approximators. In Proceedings of the 32nd International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 37) , Francis Bach and David Blei (Eds.). PMLR, Lille, France, 1312–1320
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Karol Gregor, Danilo Jimenez Rezende, and Daan Wierstra. 2016 · 2016
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Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates
Shixiang Gu, Ethan Holly, Timothy Lillicrap, and Sergey Levine. 2016 · 2016
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The CMA Evolution Strategy: A Tutorial
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Addressing Function Approximation Error in Actor-Critic Methods
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Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
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Continuous control with deep reinforcement learning
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Justin K. Pugh, Lisa B. Soros, and Kenneth O. Stanley. 2016 · 2016
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Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis. 2016 · 2016
Cited alongside, same era.
Reset-free Trial-and-Error Learning for Robot Damage Recovery
Konstantinos Chatzilygeroudis, Vassilis Vassiliades, and Jean-Baptiste Mouret. 2018 · 2017
Cited alongside, same era.
Quality and Diversity Optimization: A Unifying Modular Framework
Antoine Cully and Yiannis Demiris. 2017 · 2017
Cited alongside, same era.
Population Based Training of Neural Networks
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 · 2017
Cited alongside, same era.
Vassilis Vassiliades, Konstantinos Chatzilygeroudis, and Jean-Baptiste Mouret. 2017 · 2017
Cited alongside, same era.
Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine. 2018 · 2018
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. 2022a
Cited in the paper.
Grandmaster level in StarCraft II using multi-agent reinforcement learning
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Differentiable Quality Diversity
Matthew C. Fontaine and Stefanos Nikolaidis. 2021 · 2021
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Brax – A Differentiable Physics Engine for Large Scale Rigid Body Simulation
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, and Olivier Bachem. 2021 · 2021
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Policy gradient assisted MAP-Elites. In Proceedings of the Genetic and Evolutionary Computation Conference . ACM, Lille France, 866–875
Olle Nilsson and Antoine Cully. 2021 · 2021
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The Difficulty of Passive Learning in Deep Reinforcement Learning
Georg Ostrovski, Pablo Samuel Castro, and Will Dabney. 2021 · 2021
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Covariance Matrix Adaptation MAP-Annealing
Matthew C. Fontaine and Stefanos Nikolaidis. 2023 · 2023
Closest in time.
Evolving Populations of Diverse RL Agents with MAP-Elites
Thomas Pierrot and Arthur Flajolet. 2023 · 2023
Closest in time.