Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System

5 March 2019

Papers citing "Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System"

11 / 11 papers shown

Title
Nash Equilibrium and Learning Dynamics in Three-Player Matching $m$ -Action Games Yuma Fujimoto Kaito Ariu Kenshi Abe 29 1 0 16 Feb 2024
Alternating Mirror Descent for Constrained Min-Max Games Andre Wibisono Molei Tao Georgios Piliouras 37 14 0 08 Jun 2022
The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model Shuyue Hu Chin-wing Leung Ho-fung Leung Harold Soh 30 4 0 03 Mar 2022
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 50 8 0 10 Nov 2021
Which priors matter? Benchmarking models for learning latent dynamics Aleksandar Botev Andrew Jaegle Peter Wirnsberger Daniel Hennes I. Higgins AI4CE 40 28 0 09 Nov 2021
Constants of Motion: The Antidote to Chaos in Optimization and Game Dynamics Georgios Piliouras Xiao Wang 39 0 0 08 Sep 2021
Learning in Matrix Games can be Arbitrarily Complex Gabriel P. Andrade Rafael Frongillo Georgios Piliouras 15 31 0 05 Mar 2021
The Evolutionary Dynamics of Independent Learning Agents in Population Games Shuyue Hu Chin-wing Leung Ho-fung Leung Harold Soh AI4CE 27 3 0 29 Jun 2020
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games Lampros Flokas Emmanouil-Vasileios Vlatakis-Gkaragkounis Georgios Piliouras MLT 24 41 0 28 Oct 2019
Differentiable Game Mechanics Alistair Letcher David Balduzzi S. Racanière James Martens Jakob N. Foerster K. Tuyls T. Graepel 42 79 0 13 May 2019
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile P. Mertikopoulos Bruno Lecouat Houssam Zenati Chuan-Sheng Foo V. Chandrasekhar Georgios Piliouras 43 292 0 07 Jul 2018