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TZID:Asia/Jerusalem
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BEGIN:VEVENT
UID:17@web.iem.technion.ac.il
DTSTART;TZID=Asia/Jerusalem:20201028T113000
DTEND;TZID=Asia/Jerusalem:20201028T123000
DTSTAMP:20201109T060748Z
URL:https://web.iem.technion.ac.il/site/iemevents/when-both-players-choose
-dominated-actions-underweighting-rare-events-in-2-player-repeated-games/
SUMMARY:When both players choose dominated actions: Underweighting rare eve
nts in 2-player repeated games [ \n Game Theory Seminar\n Seminars
\n \n ]
DESCRIPTION:By: Ori Plonsky\n Advisors: \n Where: Zoom From:\nTechnion\nA
bstract:\n\nBehavioral decision studies of individuals who make repeated d
ecisions with feedback reveal robust evidence that people behave as if the
y believe “it won’t happen to me”\, a phenomenon coined underweighti
ng of rare events. We experimentally show that the tendency to underweight
rare events persists in 2-person repeated games with stochastic payoffs\,
and that other agents can learn to exploit it. In a simultaneous-move asy
mmetric 2x2 game\, most row players consistently choose a stochastically d
ominated action that provides a better payoff most of the time but on aver
age leads to a large loss over the equilibrium prediction\, behavior consi
stent with underweighting of the rare event. In response\, most column pla
yers learn to exploit this bias by choosing a strictly dominated action th
at is worse for the row players on average but better most of the time. Th
at is\, due to underweighting of rare events by the row players\, most dya
ds converge to a profile of two dominated strategies. A second study rules
out different explanations like boredom\, altruism or risk seeking.\n\nJo
int work with Yefim Roth (University of Haifa)\n\nLink to Seminar Zoom
CATEGORIES:Game Theory Seminar,Seminars
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BEGIN:VEVENT
UID:23@web.iem.technion.ac.il
DTSTART;TZID=Asia/Jerusalem:20201111T113000
DTEND;TZID=Asia/Jerusalem:20201111T123000
DTSTAMP:20201109T060933Z
URL:https://web.iem.technion.ac.il/site/iemevents/an-algorithmic-framework
-for-approximating-maximin-share-allocation-of-chores/
SUMMARY:An Algorithmic Framework for Approximating Maximin Share Allocation
of Chores [ \n Game Theory Seminar\n Seminars\n \n ]
DESCRIPTION:By: Xin Huang\n Advisors: \n Where: ZOOM From:\nTechnion\nAbst
ract:\n\nIn this paper\, we consider the problem of how to fairly dividing
m indivisible chores among n agents. The fairness measure we considered h
ere is the maximin share. The previous best known result is that there alw
ays exists a 4/3 approximation maximin share allocation. With our algorit
hm\, we can always find a 11/9 approximation maximin share allocation for
any instance. We also discuss how to improve the efficiency of the algorit
hm and its connection to the job scheduling problem.\n\nSeminar Zoom Link
CATEGORIES:Game Theory Seminar,Seminars
END:VEVENT
BEGIN:VEVENT
UID:28@web.iem.technion.ac.il
DTSTART;TZID=Asia/Jerusalem:20201125T113000
DTEND;TZID=Asia/Jerusalem:20201125T123000
DTSTAMP:20201118T173908Z
URL:https://web.iem.technion.ac.il/site/iemevents/fair-cake-division/
SUMMARY:Fair Cake Division [ \n Game Theory Seminar\n Seminars\n
\n ]
DESCRIPTION:By: Nidhi Rathi \n Advisors: \n Where: ZOOM From:\nthe Indian
Institute of Science\nAbstract:\n\nThe classic cake-cutting problem provid
es a model for addressing fair allocation of a divisible resource (metapho
rically\, the cake) among agents with distinct preferences. Envy-free (fai
r) cake divisions with contiguous pieces are known to exist under mild con
ditions\, but it is computationally hard to find them. In this talk\, I wi
ll present two of my recent results which complements these existential (a
nd non-constructive) guarantees by developing polynomial-time approximatio
n algorithms and by identifying computationally tractable instances for fa
ir cake division. First\, I will discuss an efficient algorithm for findin
g a cake division whose envy is multiplicatively bounded by 1/3. Moving fo
rward\, I will present a result that develops efficient cake-cutting algor
ithms to find envy-free divisions for a broad class of valuations (that sa
tisfies the monotone likelihood ratios property). In particular\, our algo
rithmic result holds when the agents' valuations are induced by linear tra
nslations of any log-concave function\, such as Gaussian\, exponential\, l
inear\, or binomial.\n\n \;\n\nJoint work with Siddharth Barman\, Eshw
ar Ram Arunchaleswaran and Rachitesh Kumar\n\n \;\n\nZoom Link
CATEGORIES:Game Theory Seminar,Seminars
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DTSTART:20201025T010000
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