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DTSTAMP:20230416T170958Z
UID:4C2ADBA7-C281-4838-83F4-4DE2F36C0A53
DTSTART;TZID=America/Denver:20230413T190000
DTEND;TZID=America/Denver:20230413T203000
DESCRIPTION:The web of interconnections between today's technology and soci
 ety is upending many traditional ways of doing things:\n\nThe internet of 
 things\, bitcoin\, the sharing economy\, and connected autonomous vehicles
  are increasingly in the public mind.\n\nAs such\, computer scientists and
  engineers must be increasingly conscious of the interplay between the tec
 hnical performance of their systems and the personal objectives of users\,
  customers\, and adversaries.\n\nDr Brown will present recent work studyin
 g the design tradeoffs faced by a planner who wishes to influence and opti
 mize the behavior of a group of self-interested individuals.\n\nA key goal
  is to balance the potential benefits of implementing a given behavior-inf
 luencing scheme with its potential costs\; seeking to systematically avoid
  schemes which are likely to create perverse incentives.\n\nDr. Brown will
  explore these concepts in two contexts: routing of autonomous vehicles in
  mixed-autonomy transportation networks and decision design for communicat
 ion-denied distributed multiagent systems.\n\nHe will ask "when is altruis
 m good?" through the lens of the Price of Anarchy and a new conceptual fra
 mework that is termed the "Perversity Index\," which captures the potentia
 l harm that an incentive scheme may cause.\n\nUltimately\, this work seeks
  to develop foundations for a theory of robust socially-networked systems 
 which leverages the decision processes of automated components to enhance 
 overall system reliability and performance.\n\nSpeaker(s): Dr. Philip Brow
 n\, \n\nVirtual: https://events.vtools.ieee.org/m/353554
LOCATION:Virtual: https://events.vtools.ieee.org/m/353554
ORGANIZER:genef@ieee.org
SEQUENCE:7
SUMMARY:When is "Altruism" Good in Distributed Decision Making
URL;VALUE=URI:https://events.vtools.ieee.org/m/353554
X-ALT-DESC:Description: <br /><p><span style="font-size: 12pt\;"><strong>Th
 e web of interconnections between today's technology and society is upendi
 ng many traditional ways of doing things:</strong></span></p>\n<p><em>The 
 <strong>internet of things</strong></em>\, <strong><em>bitcoin</em></stron
 g>\, <strong><em>the sharing economy</em></strong>\, and <strong><em>conne
 cted autonomous vehicles</em></strong> are increasingly in the public mind
 .</p>\n<p>As such\, computer scientists and engineers must be increasingly
  conscious of the <strong>interplay</strong> between the <strong>technical
 </strong> <strong>performance</strong> of their systems and the <strong>pe
 rsonal objectives</strong> of users\, customers\, and adversaries.</p>\n<p
 >Dr Brown will present recent work studying <strong>the design tradeoffs</
 strong> faced by a <strong>planner who wishes to influence and optimize th
 e behavior of a group of self-interested individuals. </strong></p>\n<p>A 
 key <strong>goal</strong> is to <strong>balance the potential benefits</st
 rong> of implementing a given <strong>behavior-influencing scheme</strong>
  with its <strong>potential costs</strong>\; seeking to <strong>systematic
 ally avoid schemes which are likely to create perverse incentives</strong>
 .</p>\n<p>Dr. Brown will explore these concepts in two contexts: <strong>r
 outing of autonomous vehicles in mixed-autonomy transportation networks </
 strong>and <strong>decision design for communication-denied distributed mu
 ltiagent systems</strong>.</p>\n<p>He will ask <strong>"when is altruism g
 ood?"</strong> through the lens of the <strong>Price of Anarchy</strong> a
 nd a<strong> new conceptual framework that is termed the "Perversity Index
 \,"</strong> which <strong>captures the potential harm that an incentive s
 cheme may cause. </strong></p>\n<p>Ultimately\, this work seeks to <strong
 >develop foundations for a theory of robust socially-networked systems</st
 rong> which leverages <strong>the decision processes of automated componen
 ts to enhance overall system reliability and performance.</strong></p>
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