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Research map / Learning theory and algorithms / Submodular and game algorithms

Coarse Correlation in Extensive-Form Games

AAAI 2020 · Learning theory and algorithms › Submodular and game algorithms · approach: Correlated equilibria in sequential games

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the NFCCE linear-programming formulation instead of prior column-generation algorithmsSocial-welfare-maximizing NFCCE · Sheriff, Battleship, Goofspielruntime: two to four orders of magnitude fasterHelped
Use the NFCCE linear-programming formulation instead of prior column-generation algorithmsSocial-welfare-maximizing NFCCE · Sheriff, Battleship, Goofspielscalable instance size: up to five orders of magnitude largerHelped
Use EFCCE instead of EFCESocial-welfare-maximizing equilibrium computation · Sheriff, Battleship, Goofspielruntime: between two to four times fasterHelped
Use NFCCE instead of EFCCESocial-welfare-maximizing equilibrium computation · Sheriff, Battleship, Goofspielruntime: up to four times fasterHelped
Increase equilibrium coarseness from EFCE through EFCCE to NFCCESocial-welfare-maximizing correlated equilibrium · Battleship, Sheriffmaximum social welfareHelped
Increase equilibrium coarseness from EFCE through EFCCE to NFCCESocial-welfare-maximizing correlated equilibrium · Goofspielmaximum social welfareNo clear effect
Use EFCCE instead of EFCESocial-welfare-maximizing correlated equilibrium · Experimental game instancesmaximum social welfareNo clear effect

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