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UID:20251008T033656EDT-9876OdVvUx@132.216.98.100
DTSTAMP:20251008T073656Z
DESCRIPTION:Title: Finding Nash equilibria in random win-lose games\n\nAbst
 ract: Finding a Nash equilibrium in large two-person games is known to be 
 computationally hard in the worst case. In this talk we discuss whether in
  'typical' games this is still the case. In particular\, we consider rando
 m win-lose games\, where the entries of the payoff matrices are independen
 t Bernoulli random variables with parameter p. We show that for a wide ran
 ge of values of the parameter p\, there is an expected polynomial time alg
 orithm that computes a Nash equilibrium. The talk is based on joint work w
 ith Andrea Collevecchio\, Adrian Vetta\, and Rui-Ray Zhang.\n\nZoom Link: 
 https://umontreal.zoom.us/j/87805116449?pwd=Zqn2bGupljZwDftmU9iiAi7kpHMXaF
 .1\n
DTSTART:20241010T153000Z
DTEND:20241010T163000Z
LOCATION:Room 719A\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Gábor Lugosi (Universitat Pompeu Fabra)
URL:/mathstat/channels/event/gabor-lugosi-universitat-
 pompeu-fabra-360215
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