2 citations · 4 across the 6 of their papers we have counts for
6 papers
Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem
Raphael Koster, Miruna Pîslar, Andrea Tacchetti +7
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.…
Approximating the Core via Iterative Coalition Sampling
Ian Gemp, Marc Lanctot, Luke Marris +11
The core is a central solution concept in cooperative game theory, defined as the set of feasible allocations or payments such that no subset of agents has incentive to break away…
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…
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, David C. Parkes, Ian Gemp +5
We introduce the use of generative adversarial learning to compute equilibria in general game-theoretic settings, specifically the generalized Nash equilibrium (GNE) in pseudo-game…
Learning Correlated Equilibria in Mean-Field Games
Paul Muller, Romuald Elie, Mark Rowland +7
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts. However, as the size of an -player…
Regularity of BSDEs with a convex constraint on the gains-process
Bruno Bouchard, Romuald Elie, Ludovic Moreau
We consider the minimal super-solution of a backward stochastic differential equation with constraint on the gains-process. The terminal condition is given by a function of the ter…