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Comparing natural evolution strategies to BIPOP-CMA-ES on noiseless and noisy black-box optimization testbeds.. GECCO (Companion), стр. 237-244. ACM, (2012)Investigating the impact of adaptation sampling in natural evolution strategies on black-box optimization testbeds.. GECCO (Companion), стр. 221-228. ACM, (2012)Benchmarking natural evolution strategies with adaptation sampling on the noiseless and noisy black-box optimization testbeds.. GECCO (Companion), стр. 229-236. ACM, (2012)Learning to learn by gradient descent by gradient descent., , , , , , и . NIPS, стр. 3981-3989. (2016)Natural Value Approximators: Learning when to Trust Past Estimates., , , , , и . NIPS, стр. 2120-2128. (2017)Dueling Network Architectures for Deep Reinforcement Learning., , , , , и . ICML, том 48 из JMLR Workshop and Conference Proceedings, стр. 1995-2003. JMLR.org, (2016)Dueling Network Architectures for Deep Reinforcement Learning, , , , , и . (2015)cite arxiv:1511.06581Comment: 15 pages, 5 figures, and 5 tables.Prioritized Experience Replay, , , и . (2015)cite arxiv:1511.05952Comment: Published at ICLR 2016.Q-Error as a Selection Mechanism in Modular Reinforcement-Learning Systems., и . IJCAI, стр. 1452-1457. IJCAI/AAAI, (2011)Return-based Scaling: Yet Another Normalisation Trick for Deep RL., , , и . CoRR, (2021)