Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Biess, Armin"'
Motion planning is still an open problem for many disciplines, e.g., robotics, autonomous driving, due to their need for high computational resources that hinder real-time, efficient decision-making. A class of methods striving to provide smooth solu
Externí odkaz:
http://arxiv.org/abs/2309.15970
Autor:
Manela, Binyamin, Biess, Armin
Learning complex tasks from scratch is challenging and often impossible for humans as well as for artificial agents. A curriculum can be used instead, which decomposes a complex task (target task) into a sequence of source tasks (the curriculum). Eac
Externí odkaz:
http://arxiv.org/abs/2008.09377
The technological and scientific challenges involved in the development of autonomous vehicles (AVs) are currently of primary interest for many automobile companies and research labs. However, human-controlled vehicles are likely to remain on the roa
Externí odkaz:
http://arxiv.org/abs/2006.04218
The development of autonomous robotic systems that can learn from human demonstrations to imitate a desired behavior - rather than being manually programmed - has huge technological potential. One major challenge in imitation learning is the correspo
Externí odkaz:
http://arxiv.org/abs/2003.02638
We introduce a framework for performing regression between two Hilbert spaces. This is done based on Kirszbraun's extension theorem, to the best of our knowledge, the first application of this technique to supervised learning. We analyze the statisti
Externí odkaz:
http://arxiv.org/abs/1905.11930
Autor:
Manela, Binyamin, Biess, Armin
Hindsight Experience Replay (HER) is a multi-goal reinforcement learning algorithm for sparse reward functions. The algorithm treats every failure as a success for an alternative (virtual) goal that has been achieved in the episode. Virtual goals are
Externí odkaz:
http://arxiv.org/abs/1905.05498
Most of industrial robotic assembly tasks today require fixed initial conditions for successful assembly. These constraints induce high production costs and low adaptability to new tasks. In this work we aim towards flexible and adaptable robotic ass
Externí odkaz:
http://arxiv.org/abs/1809.10699
Autor:
Zaichyk, Hananel1 (AUTHOR), Biess, Armin1 (AUTHOR), Kontorovich, Aryeh1 (AUTHOR) karyeh@bgu.ac.il, Makarychev, Yury2 (AUTHOR)
Publikováno v:
Mathematical Programming. Sep2024, Vol. 207 Issue 1/2, p617-642. 26p.
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