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UID:/NewsandEvents/Archives/2007/newsitem/1771/15-
 March-2007-Logics-for-Dynamics-of-Information-and-
 Preferences---Special-Working-sessions-François-Le
 page-Universite-de-Montreal-
DTSTAMP:20070308T000000
SUMMARY:Logics for Dynamics of Information and Pre
 ferences - Special Working sessions, François Lepa
 ge (Universite de Montreal)
ATTENDEE;ROLE=Speaker:François Lepage (Universite 
 de Montreal)
DTSTART;TZID=Europe/Amsterdam:20070315T140000
DTEND;TZID=Europe/Amsterdam:20070315T000000
LOCATION:P3.27, Euclides Building, Plantage Muider
 gracht 24, Amsterdam
DESCRIPTION:There are two very different ways to r
 epresent the dynamics of belief. One is the well k
 nown conditionalization: An agent whose belief fun
 ction is represented by a probability function Pr(
 X) shifts to Pr(X ∧ A)/Pr(A) after discovering tha
 t A is the case. An other kind of dynamics is asso
 ciated with the evaluation of a counterfactual: Pr
 (A > B) = Pr_A(B) where Pr_A is obtained from Pr b
 y some minimal change to obtain Pr _A(A) = 1. This
  is Imaging as introduced by David Lewis.    After
  a characterization of Lewis imaging, we ask the q
 uestion of the possibility of extending imaging to
  the general framework of conditional probability 
 functions, i.e. of the possibility of defining - g
 iven that conditional probability function Pr(X, Γ
 ) is the primitive notion - Pr(A > B,Γ) using imag
 ing. We show that there is no simple and intuitive
  way to do so.    For more information, see http:/
 /staff.science.uva.nl/~oroy/Working_sessions/
X-ALT-DESC;FMTTYPE=text/html:\n      <p>There are 
 two very different ways to represent the dynamics 
 of belief. One is the well known conditionalizatio
 n: An agent whose belief function is represented b
 y a probability\n        function Pr(X) shifts to 
 Pr(X &#8743; A)/Pr(A)\n        after discovering t
 hat A is the case. An other kind of\n        dynam
 ics is associated with the evaluation of a counter
 factual: Pr(A &gt; B) = Pr_A(B) where Pr_A is obta
 ined from Pr by some minimal change to obtain Pr _
 A(A) = 1. This is Imaging as introduced by David L
 ewis.\n    </p>\n    <p>\n        After a characte
 rization of Lewis imaging, we ask the question of 
 the possibility of extending imaging to the genera
 l framework of conditional probability functions, 
 i.e. of the possibility of defining - given that c
 onditional probability function Pr(X, &#915;) is t
 he primitive notion - Pr(A &gt; B,&#915;) using im
 aging. We show that there is no simple and intuiti
 ve way to do so.\n      </p>\n    \n      <p>\n   
      For more information, see <a target="_blank" 
 href="http://staff.science.uva.nl/~oroy/Working_se
 ssions/">http://staff.science.uva.nl/~oroy/Working
 _sessions/</a>\n      </p>\n    
URL:/NewsandEvents/Archives/2007/newsitem/1771/15-
 March-2007-Logics-for-Dynamics-of-Information-and-
 Preferences---Special-Working-sessions-François-Le
 page-Universite-de-Montreal-
END:VEVENT
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