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pro vyhledávání: '"Gross, Roderich"'
This paper studies how groups of robots can effectively navigate through a crowd of agents. It quantifies the performance of platooning and less constrained, greedy strategies, and the extent to which these strategies disrupt the crowd agents. Three
Externí odkaz:
http://arxiv.org/abs/2410.14406
Publikováno v:
Published in Benelearn/BANIC 2018
Save for some special cases, current training methods for Generative Adversarial Networks (GANs) are at best guaranteed to converge to a `local Nash equilibrium` (LNE). Such LNEs, however, can be arbitrarily far from an actual Nash equilibrium (NE),
Externí odkaz:
http://arxiv.org/abs/1806.07268
Autor:
Oliehoek, Frans A., Savani, Rahul, Gallego-Posada, Jose, van der Pol, Elise, de Jong, Edwin D., Gross, Roderich
Generative Adversarial Networks (GAN) have become one of the most successful frameworks for unsupervised generative modeling. As GANs are difficult to train much research has focused on this. However, very little of this research has directly exploit
Externí odkaz:
http://arxiv.org/abs/1712.00679
Publikováno v:
In Aerospace Science and Technology January 2022 120
Publikováno v:
Swarm Intelligence, 10(3):211-243, 2016
We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of th
Externí odkaz:
http://arxiv.org/abs/1603.04904
Autor:
Gross, Roderich
We look at robotic systems made of separate discrete components that, by self-assembling, can organize into physical structures of growing size. We review 22 such systems, exhibiting components ranging from passive mechanical parts to mobilerobots. W
Autor:
Groß, Roderich
We look at robotic systems made of separate discrete components that, by self-assembling, can organize into physical structures of growing size. We review 22 such systems, exhibiting components ranging from passive mechanical parts to mobile robots.
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