Generalized mirror descents with non-convex potential functions in atomic congestion games: continuous time and discrete time

DOI10.1016/j.ipl.2017.10.003zbMath1419.68222OpenAlexW2766686929MaRDI QIDQ1679909

Po-An Chen

Publication date: 22 November 2017

Published in: Information Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ipl.2017.10.003

zbMATH Keywords

convergenceanalysis of algorithmscongestion gamesmirror descentsnonconvex potential function

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Applications of game theory (91A80)

Cites Work

• Generalized mirror descents in congestion games
• Load balancing without regret in the bulletin board model
• Mirror descent and nonlinear projected subgradient methods for convex optimization.
• On the convergence of regret minimization dynamics in concave games
• Multiplicative updates outperform generic no-regret learning in congestion games
• Routing without regret
• Tatonnement beyond gross substitutes?

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