180 citations · 1.5k across the 49 of their papers we have counts for
14 papers · 1 filter
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.…
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…
From Motor Control to Team Play in Simulated Humanoid Football
Siqi Liu, Guy Lever, Zhe Wang +19
Intelligent behaviour in the physical world exhibits structure at multiple spatial and temporal scales. Although movements are ultimately executed at the level of instantaneous mus…
Scaling up Mean Field Games with Online Mirror Descent
Julien Perolat, Sarah Perrin, Romuald Elie +5
We address scaling up equilibrium computation in Mean Field Games (MFGs) using Online Mirror Descent (OMD). We show that continuous-time OMD provably converges to a Nash equilibriu…
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,…
The Advantage Regret-Matching Actor-Critic
Audrūnas Gruslys, Marc Lanctot, Rémi Munos +10
Regret minimization has played a key role in online learning, equilibrium computation in games, and reinforcement learning (RL). In this paper, we describe a general model-free RL…