Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Julian Schrittwieser"'
Autor:
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals
Publikováno v:
Science. 378:1092-1097
Programming is a powerful and ubiquitous problem-solving tool. Developing systems that can assist programmers or even generate programs independently could make programming more productive and accessible, yet so far incorporating innovations in AI ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::238ab6ad271f5cdc6e1aa0716740f3ed
https://doi.org/10.1126/science.abq1158
https://doi.org/10.1126/science.abq1158
Autor:
Finbarr Timbers, Nolan Bard, Edward Lockhart, Marc Lanctot, Martin Schmid, Neil Burch, Julian Schrittwieser, Thomas Hubert, Michael Bowling
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Researchers have shown that neural networks are vulnerable to adversarial examples and subtle environment changes. The resulting errors can look like blunders to humans, eroding trust in these agents. In prior games research, agent evaluation often f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acfb39584ec0aa74332162adf4d22b6b
https://doi.org/10.24963/ijcai.2022/484
https://doi.org/10.24963/ijcai.2022/484
Autor:
Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli
Publikováno v:
Nature. 610(7930)
Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one such primitive task, occurring in many systems—from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2c48b61ee3eb27e7453bdb1a143def2
https://pubmed.ncbi.nlm.nih.gov/36198780
https://pubmed.ncbi.nlm.nih.gov/36198780
Autor:
Demis Hassabis, Ioannis Antonoglou, Thore Graepel, Julian Schrittwieser, Timothy P. Lillicrap, Karen Simonyan, Laurent Sifre, Marc Lanctot, Thomas Hubert, Dharshan Kumaran, Matthew Lai, David Silver, Arthur Guez
Publikováno v:
Science. 362:1140-1144
One program to rule them all Computers can beat humans at increasingly complex games, including chess and Go. However, these programs are typically constructed for a particular game, exploiting its properties, such as the symmetries of the board on w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3a85e816b02d23c369533bd1597b372
https://doi.org/10.1126/science.aar6404
https://doi.org/10.1126/science.aar6404
Autor:
Karen Simonyan, Timothy P. Lillicrap, Demis Hassabis, George van den Driessche, Ioannis Antonoglou, Adrian Bolton, Yutian Chen, Fan Hui, Aja Huang, Thomas Hubert, David Silver, Arthur Guez, Laurent Sifre, Julian Schrittwieser, Lucas Baker, Thore Graepel, Matthew Lai
Publikováno v:
Nature. 550:354-359
A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in Alpha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61cb4d8e41f6fc9b81059e1e048b2a61
https://doi.org/10.1038/nature24270
https://doi.org/10.1038/nature24270
Autor:
Demis Hassabis, Simon Schmitt, Karen Simonyan, Thomas Hubert, Julian Schrittwieser, David Silver, Ioannis Antonoglou, Laurent Sifre, Arthur Guez, Timothy P. Lillicrap, Edward Lockhart, Thore Graepel
Constructing agents with planning capabilities has long been one of the main challenges in the pursuit of artificial intelligence. Tree-based planning methods have enjoyed huge success in challenging domains, such as chess1 and Go2, where a perfect s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2b9a9bea567e652943fb7da75d8e209
http://arxiv.org/abs/1911.08265
http://arxiv.org/abs/1911.08265
Autor:
John Nham, David Silver, Ilya Sutskever, Demis Hassabis, George van den Driessche, Arthur Guez, Dominik Grewe, Marc Lanctot, Thore Graepel, Laurent Sifre, Chris J. Maddison, Nal Kalchbrenner, Ioannis Antonoglou, Timothy P. Lillicrap, Koray Kavukcuoglu, Julian Schrittwieser, Madeleine Leach, Aja Huang, Veda Panneershelvam, Sander Dieleman
Publikováno v:
Nature. 529:484-489
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae3953e2190143a462dcebd18f7c4495
https://doi.org/10.1038/nature16961
https://doi.org/10.1038/nature16961