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Items: 7

1.

Human-level performance in 3D multiplayer games with population-based reinforcement learning.

Jaderberg M, Czarnecki WM, Dunning I, Marris L, Lever G, Castañeda AG, Beattie C, Rabinowitz NC, Morcos AS, Ruderman A, Sonnerat N, Green T, Deason L, Leibo JZ, Silver D, Hassabis D, Kavukcuoglu K, Graepel T.

Science. 2019 May 31;364(6443):859-865. doi: 10.1126/science.aau6249.

PMID:
31147514
2.

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

Silver D, Hubert T, Schrittwieser J, Antonoglou I, Lai M, Guez A, Lanctot M, Sifre L, Kumaran D, Graepel T, Lillicrap T, Simonyan K, Hassabis D.

Science. 2018 Dec 7;362(6419):1140-1144. doi: 10.1126/science.aar6404.

PMID:
30523106
3.

Symmetric Decomposition of Asymmetric Games.

Tuyls K, Pérolat J, Lanctot M, Ostrovski G, Savani R, Leibo JZ, Ord T, Graepel T, Legg S.

Sci Rep. 2018 Jan 17;8(1):1015. doi: 10.1038/s41598-018-19194-4.

4.

Mastering the game of Go without human knowledge.

Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M, Bolton A, Chen Y, Lillicrap T, Hui F, Sifre L, van den Driessche G, Graepel T, Hassabis D.

Nature. 2017 Oct 18;550(7676):354-359. doi: 10.1038/nature24270.

PMID:
29052630
5.

Mastering the game of Go with deep neural networks and tree search.

Silver D, Huang A, Maddison CJ, Guez A, Sifre L, van den Driessche G, Schrittwieser J, Antonoglou I, Panneershelvam V, Lanctot M, Dieleman S, Grewe D, Nham J, Kalchbrenner N, Sutskever I, Lillicrap T, Leach M, Kavukcuoglu K, Graepel T, Hassabis D.

Nature. 2016 Jan 28;529(7587):484-9. doi: 10.1038/nature16961.

PMID:
26819042
6.

Private traits and attributes are predictable from digital records of human behavior.

Kosinski M, Stillwell D, Graepel T.

Proc Natl Acad Sci U S A. 2013 Apr 9;110(15):5802-5. doi: 10.1073/pnas.1218772110. Epub 2013 Mar 11.

7.

A stochastic self-organizing map for proximity data.

Graepel T, Obermayer K.

Neural Comput. 1999 Jan 1;11(1):139-55.

PMID:
9950727

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