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

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

James P. Bailey
Georgios Piliouras
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Papers citing "Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System"

4 / 4 papers shown
Title
The Hamiltonian of Poly-matrix Zero-sum Games
The Hamiltonian of Poly-matrix Zero-sum Games
Toshihiro Ota
Yuma Fujimoto
AI4CE
62
0
0
19 May 2025
Nash Equilibrium and Learning Dynamics in Three-Player Matching $m$-Action Games
Nash Equilibrium and Learning Dynamics in Three-Player Matching mm-Action Games
Yuma Fujimoto
Kaito Ariu
Kenshi Abe
39
1
0
16 Feb 2024
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games
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
53
41
0
28 Oct 2019
Introduction to Online Convex Optimization
Introduction to Online Convex Optimization
Elad Hazan
OffRL
108
1,922
0
07 Sep 2019