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Bio
I conduct research in deep learning, including deep reinforcement learning. I improve our understanding of deep neural networks, harness them in novel applications (such as helping biologists conserve and better understand wildlife), and advance deep reinforcement learning, especially improving its ability to intelligently explore.
I have long been interested in creating open-ended algorithms and AI-generating algorithms, wherein AI systems could learn and truly innovate without end (as natural evolution and human culture do). To produce such algorithms, I study open questions in evolutionary biology regarding how intelligence evolved and try to harness those discoveries to improve our ability to produce more complex, intelligent artificial intelligence. Such work has led my colleagues and I to develop quality-diversity algorithms, which like nature do not seek to produce a single, best solution, but instead produce a vast diversity of high-quality entities.
I have long been interested in creating open-ended algorithms and AI-generating algorithms, wherein AI systems could learn and truly innovate without end (as natural evolution and human culture do). To produce such algorithms, I study open questions in evolutionary biology regarding how intelligence evolved and try to harness those discoveries to improve our ability to produce more complex, intelligent artificial intelligence. Such work has led my colleagues and I to develop quality-diversity algorithms, which like nature do not seek to produce a single, best solution, but instead produce a vast diversity of high-quality entities.
Research Interests
Papers共 136 篇Author StatisticsCo-AuthorSimilar Experts
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Yoshua Bengio,Geoffrey Hinton, Andrew Yao,Dawn Song,Pieter Abbeel,Trevor Darrell, Yuval Noah Harari,Ya-Qin Zhang, Lan Xue,Shai Shalev-Shwartz,Gillian Hadfield,Jeff Clune,
Science (New York, N.Y.)no. 6698 (2024): 842-845
CoRR (2024)
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SIMA Team, Maria Abi Raad,Arun Ahuja, Catarina Barros,Frederic Besse, Andrew Bolt,Adrian Bolton, Bethanie Brownfield,Gavin Buttimore, Max Cant, Sarah Chakera,Stephanie C. Y. Chan,
CoRR (2024)
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CoRR (2023)
ICLR 2024 (2023)
NeurIPS (2023)
Ben Norman,Jeff Clune
CoRR (2023)
NeurIPS 2022 (2022)
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