no code implementations • 23 Apr 2024 • Raphael Koster, Miruna Pîslar, Andrea Tacchetti, Jan Balaguer, Leqi Liu, Romuald Elie, Oliver P. Hauser, Karl Tuyls, Matt Botvinick, Christopher Summerfield
A canonical social dilemma arises when finite resources are allocated to a group of people, who can choose to either reciprocate with interest, or keep the proceeds for themselves.
no code implementations • 16 Oct 2023 • Zhe Wang, Petar Veličković, Daniel Hennes, Nenad Tomašev, Laurel Prince, Michael Kaisers, Yoram Bachrach, Romuald Elie, Li Kevin Wenliang, Federico Piccinini, William Spearman, Ian Graham, Jerome Connor, Yi Yang, Adrià Recasens, Mina Khan, Nathalie Beauguerlange, Pablo Sprechmann, Pol Moreno, Nicolas Heess, Michael Bowling, Demis Hassabis, Karl Tuyls
The utility of TacticAI is validated by a qualitative study conducted with football domain experts at Liverpool FC.
no code implementations • 22 Sep 2022 • Ian Gemp, Thomas Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome Connor, Vibhavari Dasagi, Bart De Vylder, Edgar Duenez-Guzman, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, SiQi Liu, Luke Marris, Kevin R. McKee, Paul Muller, Julien Perolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls
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 simulating social dilemmas in rich spatial environments and training 3-d humanoids in difficult team coordination tasks.
no code implementations • 22 Aug 2022 • Paul Muller, Romuald Elie, Mark Rowland, Mathieu Lauriere, Julien Perolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts.
1 code implementation • 30 Jun 2022 • Julien Perolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas Anthony, Stephen Mcaleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent SIfre, Nathalie Beauguerlange, Remi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls
It has the additional complexity of requiring decision-making under imperfect information, similar to Texas hold'em poker, which has a significantly smaller game tree (on the order of $10^{164}$ nodes).
no code implementations • 17 Dec 2021 • Romuald Elie, Caroline Hillairet, François Hu, Marc Juillard
This paper addresses significant obstacles that arise from the widespread use of machine learning models in the insurance industry, with a specific focus on promoting fairness.
no code implementations • 28 Jun 2021 • Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome Connor, Karl Tuyls
Importantly, $\Phi$-regret enables learning agents to consider deviations from and to mixed strategies, generalizing several existing notions of regret such as external, internal, and swap regret, and thus broadening the insights gained from regret-based analysis of learning algorithms.
no code implementations • 8 Jun 2021 • Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls
In multiagent environments, several decision-making individuals interact while adhering to the dynamics constraints imposed by the environment.
no code implementations • 7 Jun 2021 • Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Mean-field Games (MFGs) are a continuous approximation of many-agent RL.
1 code implementation • 28 Feb 2021 • Julien Perolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
We address scaling up equilibrium computation in Mean Field Games (MFGs) using Online Mirror Descent (OMD).
no code implementations • 10 Feb 2021 • Carl Remlinger, Joseph Mikael, Romuald Elie
We introduce three new generative models for time series that are based on Euler discretization of Stochastic Differential Equations (SDEs) and Wasserstein metrics.
no code implementations • 1 Jan 2021 • Carl Remlinger, Joseph Mickael, Romuald Elie
A new model of generative adversarial networks for time series based on Euler scheme and Wasserstein distances including Sinkhorn divergence is proposed.
1 code implementation • 18 Nov 2020 • Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adria Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Perolat, Bart De Vylder, Ali Eslami, Mark Rowland, Andrew Jaegle, Remi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball, basketball, and tennis.
1 code implementation • NeurIPS 2020 • Sarah Perrin, Julien Perolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
In this paper, we deepen the analysis of continuous time Fictitious Play learning algorithm to the consideration of various finite state Mean Field Game settings (finite horizon, $\gamma$-discounted), allowing in particular for the introduction of an additional common noise.
no code implementations • 22 Mar 2020 • Arthur Charpentier, Romuald Elie, Carl Remlinger
As in multi-armed bandit problems, when an agent picks an action, he can not infer ex-post the rewards induced by other action choices.
no code implementations • 4 Jul 2019 • Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
In order to design scalable algorithms for systems with a large population of interacting agents (e. g. swarms), this paper focuses on Mean Field MAS, where the number of agents is asymptotically infinite.