BEGIN:VCALENDAR VERSION:2.0 PRODID:ILLC Website X-WR-TIMEZONE:Europe/Amsterdam BEGIN:VTIMEZONE TZID:Europe/Amsterdam X-LIC-LOCATION:Europe/Amsterdam BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700329T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701025T030000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT 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
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 ∧ 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 > 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
\n\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, Γ) is t he primitive notion - Pr(A > B,Γ) using im aging. We show that there is no simple and intuiti ve way to do so.\n
\n \n\n For more information, see http://staff.science.uva.nl/~oroy/Working _sessions/\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 END:VCALENDAR