activity
20192026
most citedLearning and Evaluating General Linguistic Intelligence

157 citations · 335 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

DiffusionGemma Technical Report

DiffusionGemma Team, Adrien Ali Taïga, James Assiene +41

We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rather than decoding one token at…

cs.LG2023★ 1 cited

TacticAI: an AI assistant for football tactics

Zhe Wang, Petar Veličković, Daniel Hennes +20

Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains…

cs.GT2022

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

Luke Marris, Marc Lanctot, Ian Gemp +5

Rating strategies in a game is an important area of research in game theory and artificial intelligence, and can be applied to any real-world competitive or cooperative setting. Tr…

cs.MA2022

Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments

Ian Gemp, Thomas Anthony, Yoram Bachrach +24

The Game Theory & Multi-Agent team at DeepMind studies several aspects of multi-agent learning ranging from computing approximations to fundamental concepts in game theory to simul…

cs.AI2022★ 153 cited

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

Julien Perolat, Bart de Vylder, Daniel Hennes +31

We introduce DeepNash, an autonomous agent capable of learning to play the imperfect information game Stratego from scratch, up to a human expert level. Stratego is one of the few…

cs.GT2021

Evolutionary Dynamics and -Regret Minimization in Games

Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei +4

Regret has been established as a foundational concept in online learning, and likewise has important applications in the analysis of learning dynamics in games. Regret quantifies t…

cs.LG2021★ 2 cited

Time-series Imputation of Temporally-occluded Multiagent Trajectories

Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo +8

In multiagent environments, several decision-making individuals interact while adhering to the dynamics constraints imposed by the environment. These interactions, combined with th…

cs.AI2020

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

Karl Tuyls, Shayegan Omidshafiei, Paul Muller +33

The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball,…

cs.AI2020★ 22 cited

Navigating the Landscape of Multiplayer Games

Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki +9

Multiplayer games have long been used as testbeds in artificial intelligence research, aptly referred to as the Drosophila of artificial intelligence. Traditionally, researchers ha…

cs.LG2019★ 157 cited

Learning and Evaluating General Linguistic Intelligence

Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor +8

We define general linguistic intelligence as the ability to reuse previously acquired knowledge about a language's lexicon, syntax, semantics, and pragmatic conventions to adapt to…