Thore Graepel

Thore Graepel

University College London

H-index: 72

Europe-United Kingdom

About Thore Graepel

Thore Graepel, With an exceptional h-index of 72 and a recent h-index of 50 (since 2020), a distinguished researcher at University College London, specializes in the field of Machine Learning, Reinforcement Learning, Deep Learning, Multi-Agent Learning, Computational Biology.

His recent articles reflect a diverse array of research interests and contributions to the field:

Jointly updating agent control policies using estimated best responses to current control policies

Neupl: Neural population learning

Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy

Neural network architecture for efficient resource allocation

Selecting points in continuous spaces using neural networks

Hidden agenda: a social deduction game with diverse learned equilibria

Game Theoretic Rating in N-player general-sum games with Equilibria

From motor control to team play in simulated humanoid football

Thore Graepel Information

University

Position

Research Scientist Google DeepMind and Professor of Computer Science

Citations(all)

60099

Citations(since 2020)

42711

Cited By

34363

hIndex(all)

72

hIndex(since 2020)

50

i10Index(all)

172

i10Index(since 2020)

123

Email

University Profile Page

University College London

Google Scholar

View Google Scholar Profile

Thore Graepel Skills & Research Interests

Machine Learning

Reinforcement Learning

Deep Learning

Multi-Agent Learning

Computational Biology

Top articles of Thore Graepel

Title

Journal

Author(s)

Publication Date

Jointly updating agent control policies using estimated best responses to current control policies

2024/2/8

Neupl: Neural population learning

arXiv preprint arXiv:2202.07415

Siqi Liu

Luke Marris

Daniel Hennes

Josh Merel

Nicolas Heess

...

2022/2/15

Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy

Nature Communications

János Kramár

Tom Eccles

Ian Gemp

Andrea Tacchetti

Kevin R McKee

...

2022/12/6

Neural network architecture for efficient resource allocation

2022/2/15

Selecting points in continuous spaces using neural networks

2022/11/24

Hidden agenda: a social deduction game with diverse learned equilibria

arXiv preprint arXiv:2201.01816

Kavya Kopparapu

Edgar A Duéñez-Guzmán

Jayd Matyas

Alexander Sasha Vezhnevets

John P Agapiou

...

2022/1/5

Game Theoretic Rating in N-player general-sum games with Equilibria

arXiv preprint arXiv:2210.02205

Luke Marris

Marc Lanctot

Ian Gemp

Shayegan Omidshafiei

Stephen McAleer

...

2022/10/5

From motor control to team play in simulated humanoid football

Science Robotics

Siqi Liu

Guy Lever

Zhe Wang

Josh Merel

SM Ali Eslami

...

2022/8/31

Training a policy neural network for controlling an agent using best response policy iteration

2022/8/18

Eigengame unloaded: When playing games is better than optimizing

arXiv preprint arXiv:2102.04152

Ian Gemp

Brian McWilliams

Claire Vernade

Thore Graepel

2021/2/8

Scalable evaluation of multi-agent reinforcement learning with melting pot

Joel Z Leibo

Edgar A Dueñez-Guzman

Alexander Vezhnevets

John P Agapiou

Peter Sunehag

...

2021/7/1

A Neural Network Auction For Group Decision Making Over a Continuous Space.

Yoram Bachrach

Ian M Gemp

Marta Garnelo

Janos Kramar

Tom Eccles

...

2021

Game Plan: What AI can do for Football, and What Football can do for AI

Journal of Artificial Intelligence Research

Karl Tuyls

Shayegan Omidshafiei

Paul Muller

Zhe Wang

Jerome Connor

...

2021/5/6

Inferring cues for use with digital assistant

2021/5/4

A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!

arXiv preprint arXiv:2109.13889

Thore Graepel

Ralf Herbrich

2021/9/28

Cooperative AI: machines must learn to find common ground

Allan Dafoe

Yoram Bachrach

Gillian Hadfield

Eric Horvitz

Kate Larson

...

2021/5

Checking and/or completion for data grids

2021/8/17

A multi-agent reinforcement learning model of reputation and cooperation in human groups

arXiv preprint arXiv:2103.04982

Kevin R McKee

Edward Hughes

Tina O Zhu

Martin J Chadwick

Raphael Koster

...

2021/3/8

Multi-agent training beyond zero-sum with correlated equilibrium meta-solvers

Luke Marris

Paul Muller

Marc Lanctot

Karl Tuyls

Thore Graepel

2021/7/1

Bounds and dynamics for empirical game theoretic analysis

Autonomous Agents and Multi-Agent Systems

Karl Tuyls

Julien Perolat

Marc Lanctot

Edward Hughes

Richard Everett

...

2020/4

See List of Professors in Thore Graepel University(University College London)

Co-Authors

H-index: 60
Michal Kosinski

Michal Kosinski

Stanford University

H-index: 55
Klaus Obermayer

Klaus Obermayer

Technische Universität Berlin

H-index: 49
David Stillwell

David Stillwell

University of Cambridge

H-index: 24
Chris J. Maddison

Chris J. Maddison

University of Toronto

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