BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:IC Colloquium : Games\, Equilibria\, and Evolution
DTSTART:20150302T101500
DTEND:20150302T113000
DTSTAMP:20260406T192606Z
UID:fd8e64f225be7ec0c8d0e7846d79fa798e4b445fab6b8074d190bce2
CATEGORIES:Conferences - Seminars
DESCRIPTION:By : Ruta Mehta - College of Computing\, Georgia Tech\nIC Facu
 lty candidateAbstract :\nThe tremendous growth of online markets\, ad auct
 ions\, and social network communities\, where agents interact to achieve t
 heir own goals\, often selfish\, has created a need to apply game theoreti
 c solution concepts more than ever before. In this talk I will discuss one
  of the most important solution concept in game theory\, namely Nash equil
 ibrium\, its computation and applications. Recently a remarkable connectio
 n was discovered between evolution under sexual reproduction and coordinat
 ion games. Proceeding along these lines I will show some new insights on g
 enetic diversity.\nTowards efficient computation\, finding Nash equilibriu
 m in two-player normal form game (2-Nash) is one of the most extensively s
 tudied problem.  Such a game can be represented by two payoff matrices A 
 and B\, one for each player. 2-Nash is PPAD-complete in general\, while if
  the game is zero-sum (B=-A) then it reduces to LP and hence is in P.\nExt
 ending this notion\, in 2005\, Kannan and Theobald defined rank of game (A
 \, B) as rank(A+B)\, e.g.\, rank-0 are zero-sum games. They asked for an e
 fficient algorithm for constant rank games\, where the primary difficulty 
 as disconnected solution sets\, even in rank-1 games. I will answer this q
 uestion affirmatively for rank-1 games\, and negatively for games with ran
 k three or more (unless PPAD=P)\; the status of rank-2 games remains unres
 olved. In the process I obtain a number of other results\, including a sim
 pler proof of PPAD-hardness for 2-Nash.Bio :\nDr. Ruta Mehta is a postdoct
 oral fellow in the college of computing at Georgia Tech\, working with Pro
 f. Vijay V. Vazirani. Her research lies at the intersection of theoretical
  computer science\, game theory\, and mathematical economics\, and their a
 pplications to evolution\, dynamical systems and learning. She has worked 
 on computability of equilibria\, both market and Nash\, under various sett
 ings\, and also on understanding the impact of strategic behavior in multi
 -agent situations. In addition she has explored learning economic paramete
 rs through revealed preferences\, and genetic evolution undersexual reprod
 uction.\nShe did her PhD from Indian Institute of Technology\, Bombay\, un
 der the guidance of Prof. Milind Sohoni\, and won ACM India Doctoral Disse
 rtation Award 2012. In 2014\, she was conferred the Best Postdoctoral Rese
 arch Award by CoC at Georgia Tech.More information 
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR