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SUMMARY:Eva Tardos (Cornell University) 07.11.2022
DTSTART;TZID=Europe/Berlin:20221107T163000
DTEND;TZID=Europe/Berlin:20221107T174500
DTSTAMP:20260511T222638Z
UID:ff02f1d318d547d182fc0d6236494ae5@www.econ.uni-bonn.de
CREATED:20221106T130712Z
DESCRIPTION:Over the last two decades we have developed good understanding
  how to quantify the impact of strategic user behavior on outcomes in many
  games (including traffic routing and online auctions) and showed that the
  resulting bounds extend to repeated games assuming players use a form of 
 no-regret learning to adapt to the environment. Unfortunately\, these resu
 lts do not apply when outcomes in one round effect the game in the future\
 , as is the case in many applications. In this talk\, we study this phenom
 enon in the context of a game modeling queuing systems: routers compete fo
 r servers\, where packets that do not get served need to be resent\, resul
 ting in a system where the number of packets at each round depends on the 
 success of the routers in the previous rounds. In joint work with Jason Ga
 itonde\, we analyze the resulting highly dependent random process. [...]
LAST-MODIFIED:20221130T094416Z
URL:https://www.econ.uni-bonn.de/micro/en/seminars/micro-theory-seminar/ev
 a-tardos-cornell-university-07-11.2022
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