Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Nordmoen, Jørgen"'
In modular robotics, modules can be reconfigured to change the morphology of the robot, making it able to adapt for specific tasks. However, optimizing both the body and control is a difficult challenge due to the intricate relationship between fine-
Externí odkaz:
http://arxiv.org/abs/2012.04375
In Evolutionary Robotics a population of solutions is evolved to optimize robots that solve a given task. However, in traditional Evolutionary Algorithms, the population of solutions tends to converge to local optima when the problem is complex or th
Externí odkaz:
http://arxiv.org/abs/2008.02116
Real-valued genotypes together with the variation operators, mutation and crossover, constitute some of the fundamental building blocks of Evolutionary Algorithms. Real-valued genotypes are utilized in a broad range of contexts, from weights in Artif
Externí odkaz:
http://arxiv.org/abs/2005.09380
Robots are used in more and more complex environments, and are expected to be able to adapt to changes and unknown situations. The easiest and quickest way to adapt is to change the control system of the robot, but for increasingly complex environmen
Externí odkaz:
http://arxiv.org/abs/1905.05626
Publikováno v:
Genetic and Evolutionary Computation Conference (GECCO 19), July 13-17, 2019, Prague, Czech Republic. ACM, New York, NY, USA
Overcoming robotics challenges in the real world requires resilient control systems capable of handling a multitude of environments and unforeseen events. Evolutionary optimization using simulations is a promising way to automatically design such con
Externí odkaz:
http://arxiv.org/abs/1904.03855
Publikováno v:
Nordmoen, Jørgen Nygaard, Tønnes Frostad Samuelsen, Eivind Glette, Kyrre . On Restricting Real-Valued Genotypes in Evolutionary Algorithms. Applications of Evolutionary Computation. 2021, 3-16 Springer
Externí odkaz:
http://hdl.handle.net/10852/91062
https://www.duo.uio.no/bitstream/handle/10852/91062/1/nordmoen-evoapps2021.pdf
https://www.duo.uio.no/bitstream/handle/10852/91062/1/nordmoen-evoapps2021.pdf
Publikováno v:
Nordmoen, Jørgen Halvorsen Nygaard, Tønnes Frostad Ellefsen, Kai Olav Glette, Kyrre . Evolved embodied phase coordination enables robust quadruped robot locomotion. GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference. 2019 Association for Computing Machinery (ACM)
Externí odkaz:
http://hdl.handle.net/10852/74778
https://www.duo.uio.no/bitstream/handle/10852/74778/2/nordmoen-gecco2019.pdf
https://www.duo.uio.no/bitstream/handle/10852/74778/2/nordmoen-gecco2019.pdf
Publikováno v:
Nordmoen, Jørgen Halvorsen Samuelsen, Eivind Ellefsen, Kai Olav Glette, Kyrre . Dynamic mutation in MAP-Elites for robotic repertoire generation. The 2018 Conference on Artificial Life. 2018, 598-605 MIT Press
Externí odkaz:
http://hdl.handle.net/10852/67776
https://www.duo.uio.no/bitstream/handle/10852/67776/1/nordmoen-alife2018.pdf
https://www.duo.uio.no/bitstream/handle/10852/67776/1/nordmoen-alife2018.pdf
Autor:
Gupta Alok, Avlesen Helge, Nordmoen Jørgen, Sætra L. Martin, Bentsen Mats, Yanchun, He, Anne, Fouilloux, Torsvik Tomas, Röblitz Thomas
Presentation given during the CSC GPU hackathon where NorESM/NICEST2 team worked together on the porting of BLOM on GPUs. The presentation shows the work done during the hackathon with the porting of a few routines on GPUs. The focus was not on perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68c175429bb03d3177c634ba0072c8dc
Publikováno v:
Nordmoen, Jørgen Halvorsen Veenstra, Frank Ellefsen, Kai Olav Glette, Kyrre . MAP-Elites Enables Powerful Stepping Stones and Diversity for Modular Robotics. Frontiers in Robotics and AI. 2021, 8
Frontiers in Robotics and AI
Frontiers in Robotics and AI
Externí odkaz:
http://hdl.handle.net/10852/86820
https://www.duo.uio.no/bitstream/handle/10852/86820/1/nordmoen-frontiers2021.pdf
https://www.duo.uio.no/bitstream/handle/10852/86820/1/nordmoen-frontiers2021.pdf