26 citations · 203 across the 41 of their papers we have counts for
7 papers · 1 filter
GANGs: Generative Adversarial Network Games
Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada +3
Generative Adversarial Networks (GAN) have become one of the most successful frameworks for unsupervised generative modeling. As GANs are difficult to train much research has focus…
Symmetric Decomposition of Asymmetric Games
Karl Tuyls, Julien Perolat, Marc Lanctot +6
We introduce new theoretical insights into two-population asymmetric games allowing for an elegant symmetric decomposition into two single population symmetric games. Specifically,…
Reachability Switching Games
John Fearnley, Martin Gairing, Matthias Mnich +1
We study the problem of deciding the winner of reachability switching games for zero-, one-, and two-player variants. Switching games provide a deterministic analogue of stochastic…
Lenient Multi-Agent Deep Reinforcement Learning
Gregory Palmer, Karl Tuyls, Daan Bloembergen +1
Much of the success of single agent deep reinforcement learning (DRL) in recent years can be attributed to the use of experience replay memories (ERM), which allow Deep Q-Networks…
Computing Constrained Approximate Equilibria in Polymatrix Games
Argyrios Deligkas, John Fearnley, Rahul Savani
This paper is about computing constrained approximate Nash equilibria in polymatrix games, which are succinctly represented many-player games defined by an interaction graph betwee…
LiftUpp: Support to develop learner performance
Frans A. Oliehoek, Rahul Savani, Elliot Adderton +8
Various motivations exist to move away from the simple assessment of knowledge towards the more complex assessment and development of competence. However, to accommodate such a cha…