A
Aja Huang
Researcher at Google
Publications - 7
Citations - 25215
Aja Huang is an academic researcher from Google. The author has contributed to research in topics: Reinforcement learning & Evaluation function. The author has an hindex of 6, co-authored 6 publications receiving 17318 citations.
Papers
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Journal ArticleDOI
Mastering the game of Go with deep neural networks and tree search
David Silver,Aja Huang,Chris J. Maddison,Arthur Guez,Laurent Sifre,George van den Driessche,Julian Schrittwieser,Ioannis Antonoglou,Veda Panneershelvam,Marc Lanctot,Sander Dieleman,Dominik Grewe,John Nham,Nal Kalchbrenner,Ilya Sutskever,Timothy P. Lillicrap,Madeleine Leach,Koray Kavukcuoglu,Thore Graepel,Demis Hassabis +19 more
TL;DR: Using this search algorithm, the program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0.5, the first time that a computer program has defeated a human professional player in the full-sized game of Go.
Journal ArticleDOI
Mastering the game of Go without human knowledge
David Silver,Julian Schrittwieser,Karen Simonyan,Ioannis Antonoglou,Aja Huang,Arthur Guez,Thomas Hubert,Lucas Baker,Matthew Lai,Adrian Bolton,Yutian Chen,Timothy P. Lillicrap,Fan Hui,Laurent Sifre,George van den Driessche,Thore Graepel,Demis Hassabis +16 more
TL;DR: An algorithm based solely on reinforcement learning is introduced, without human data, guidance or domain knowledge beyond game rules, that achieves superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo.
Journal ArticleDOI
Grandmaster level in StarCraft II using multi-agent reinforcement learning.
Oriol Vinyals,Igor Babuschkin,Wojciech Marian Czarnecki,Michael Mathieu,Andrew Dudzik,Junyoung Chung,David H. Choi,Richard E. Powell,Timo Ewalds,Petko Georgiev,Junhyuk Oh,Dan Horgan,Manuel Kroiss,Ivo Danihelka,Aja Huang,Laurent Sifre,Trevor Cai,John P. Agapiou,Max Jaderberg,Alexander Vezhnevets,Rémi Leblond,Tobias Pohlen,Valentin Dalibard,David Budden,Yury Sulsky,James Molloy,Tom Le Paine,Caglar Gulcehre,Ziyu Wang,Tobias Pfaff,Yuhuai Wu,Roman Ring,Dani Yogatama,Dario Wünsch,Katrina McKinney,Oliver Smith,Tom Schaul,Timothy P. Lillicrap,Koray Kavukcuoglu,Demis Hassabis,Chris Apps,David Silver +41 more
TL;DR: The agent, AlphaStar, is evaluated, which uses a multi-agent reinforcement learning algorithm and has reached Grandmaster level, ranking among the top 0.2% of human players for the real-time strategy game StarCraft II.
Journal ArticleDOI
Discovering faster matrix multiplication algorithms with reinforcement learning
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 +12 more
TL;DR: In this paper , a deep reinforcement learning approach based on AlphaZero is used to discover efficient and provably correct algorithms for the multiplication of arbitrary matrices, where the objective is finding tensor decompositions within a finite factor space.
Posted Content
Move Evaluation in Go Using Deep Convolutional Neural Networks
TL;DR: A large 12-layer convolutional neural network is trained by supervised learning from a database of human professional games that beats the traditional search program GnuGo in 97% of games, and matched the performance of a state-of-the-art Monte-Carlo tree search that simulates a million positions per move.