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Reinforcement Learning with Unsupervised Auxiliary Tasks., , , , , , and . CoRR, (2016)Comparing natural evolution strategies to BIPOP-CMA-ES on noiseless and noisy black-box optimization testbeds.. GECCO (Companion), page 237-244. ACM, (2012)Investigating the impact of adaptation sampling in natural evolution strategies on black-box optimization testbeds.. GECCO (Companion), page 221-228. ACM, (2012)Benchmarking natural evolution strategies with adaptation sampling on the noiseless and noisy black-box optimization testbeds.. GECCO (Companion), page 229-236. ACM, (2012)Dueling Network Architectures for Deep Reinforcement Learning., , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1995-2003. JMLR.org, (2016)Dueling Network Architectures for Deep Reinforcement Learning, , , , , and . (2015)cite arxiv:1511.06581Comment: 15 pages, 5 figures, and 5 tables.Prioritized Experience Replay, , , and . (2015)cite arxiv:1511.05952Comment: Published at ICLR 2016.Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017., , , , , , , , , and 9 other author(s). CoRR, (2017)Discovering Evolution Strategies via Meta-Black-Box Optimization., , , , , , , and . CoRR, (2022)Natural Value Approximators: Learning when to Trust Past Estimates., , , , , and . NIPS, page 2120-2128. (2017)