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Stochastic Search In Changing Situations.

, , , , , и . AAAI Workshops, том WS-17 из AAAI Technical Report, AAAI Press, (2017)

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Gerhard Neumann

Gerhard Neumann

Gerhard Neumann

Gerhard Neumann

Gerhard Neumann

 

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Reinforcement Learning from Multiple Sensors via Joint Representations., , , и . CoRR, (2023)Bayesian Context Aggregation for Neural Processes., , , , и . ICLR, OpenReview.net, (2021)Catching heuristics are optimal control policies., , , и . NIPS, стр. 1426-1434. (2016)Learning complex motions by sequencing simpler motion templates., , и . ICML, том 382 из ACM International Conference Proceeding Series, стр. 753-760. ACM, (2009)A probabilistic approach to robot trajectory generation., , и . Humanoids, стр. 477-483. IEEE, (2013)Learning of Non-Parametric Control Policies with High-Dimensional State Features., , и . AISTATS, том 38 из JMLR Workshop and Conference Proceedings, JMLR.org, (2015)Deriving and improving CMA-ES with information geometric trust regions., , , , и . GECCO, стр. 657-664. ACM, (2017)Contextual Policy Search for Generalizing a Parameterized Biped Walking Controller., , , , и . ICARSC, стр. 17-22. IEEE, (2015)Sample-based informationl-theoretic stochastic optimal control., , , и . ICRA, стр. 3896-3902. IEEE, (2014)Compatible natural gradient policy search., , , , и . Mach. Learn., 108 (8-9): 1443-1466 (2019)