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A fascinating aspect of nature lies in its ability to produce a large and diverse collection of organisms that are all high-performing in their niche.
Policy gradient methods for reinforcement learning with function approximation.. In NIPs , Vol. 99. Citeseer, 1057–1063
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Discovering the Elite Hypervolume by Leveraging Interspecies Correlation
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Empowering quality diversity in dungeon design with interactive constrained MAP-Elites. In 2019 IEEE Conference on Games (CoG) . IEEE, 1–8
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Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric Xing, Sergey Levine, and Ruslan Salakhutdinov. 2019 · 2019
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Anirudh Vemula, Wen Sun, and J Bagnell. 2019 · 2019
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Scaling MAP-Elites to deep neuroevolution. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference . 67–75
Cédric Colas, Vashisht Madhavan, Joost Huizinga, and Jeff Clune. 2020 · 2020
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Population-Guided Parallel Policy Search for Reinforcement Learning. In International Conference on Learning Representations
Whiyoung Jung, Giseung Park, and Youngchul Sung. 2020 · 2020
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Effective Diversity in Population-Based Reinforcement Learning. In Neural Information Processing Systems
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Differentiable Quality Diversity
Matthew C. Fontaine and Stefanos Nikolaidis. 2021 · 2021
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Policy Gradient Assisted MAP-Elites; Policy Gradient Assisted MAP-Elites
Olle Nilsson and Antoine Cully. 2021 · 2021
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