Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Nicholas Ketz"'
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 6, p e1003067 (2013)
The learning mechanism in the hippocampus has almost universally been assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of memories later. However, it is
Externí odkaz:
https://doaj.org/article/374cfa1ccbce4ddb956f416a74883f52
Autor:
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M.R. Arnold, Ese Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
Publikováno v:
Neural Networks. 160:274-296
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original t
Autor:
Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero-Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava Siegelmann
Publikováno v:
Nature Machine Intelligence. 4:196-210
ispartof: NATURE MACHINE INTELLIGENCE vol:4 issue:3 pages:196-210 status: published
Publikováno v:
Lecture Notes in Computer Science
TAROS 2022-Towards Autonomous Robotic Systems
TAROS 2022-Towards Autonomous Robotic Systems, 2022, Abingdon, United Kingdom. pp.266-281, ⟨10.1007/978-3-031-15908-4_21⟩
Towards Autonomous Robotic Systems ISBN: 9783031159077
TAROS 2022-Towards Autonomous Robotic Systems
TAROS 2022-Towards Autonomous Robotic Systems, 2022, Abingdon, United Kingdom. pp.266-281, ⟨10.1007/978-3-031-15908-4_21⟩
Towards Autonomous Robotic Systems ISBN: 9783031159077
International audience; Reinforcement learning agents are unable to respond effectively when faced with novel, out-of-distribution events until they have undergone a significant period of additional training. For lifelong learning agents, which canno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3112823be0e62d18ee10720f7c957223
https://inria.hal.science/hal-03949106/file/TAROS2022.pdf
https://inria.hal.science/hal-03949106/file/TAROS2022.pdf