rich bfjgyyrpxggbneiuedu dear lotfi years seen fuzzy theory used improperly practitioners use model problems modeled probability theory researchers come along slam fuzzy theory probability used model problem difficulty however fuzzy theory way applied related fashion recall special workshop gmu mid90s researchers showed calculations fuzzy theory probability theory certain independencedependence assumptions concluded probability theory subsumes fuzzy theory true theories model kind problems explain difference students 1 pick dog random kennel containing 5 collies 5 beagles probability picking collie 5 picking dog uncertainty 5 removed know certain kind dog 2 come across dog whose mother collie whose father beagle dog fuzzy set membership 5 class collies removing fuzzy membership use 1 metaphor problem problem probability use 2 metaphor problem fuzzy set theory best rich 0637 pm 10232006 lotfi zadeh wrote dear aleks thank insightful comment comment reflects prevailing viewa strongly held belief standard probability theory needed deal kind uncertainty issue related uncertainty eg issue determinism vs chance eloquent exponent view professor dennis lindley eminent bayesian good friend view dissent years written many papers issue sufficiency probability theory recently generalized theory uncertainty gtu principal concepts ideas appear computational statistics data analysis available upon request widely unrecognized standard bivalentlogicbased probability theory simply probability theory serious limitations specifically probability theory address issue partiality truth possibility class membership well partiality concepts randomness determinism chance many others probability theory provide tools dealing perceptionbased information concomitantly information described natural language implies would able construct bayesian model valentinas example underlying information perceptionbased would construct bayesian model following problem box contains balls various sizes perceptions 20 balls box b small c several times many small balls large balls probability ball drawn random neither large small another problem x realvalued random variable know x usually x much larger approximately b usually x much smaller approximately b less b expected value x probability theory differentiate probability possibility case point let x number passengers car know car fivepassenger sedan understanding possible squeeze five passengers car probability x 3 probability x 6 probability theory differentiate imprecision uncertainty would handle following simple problema problem similar stated earlier message usually takes hour drive home airport left house l0 morning time would arrive airport conclusion course long history probability theory scored many brilliant successes mean need enrichment conceptual structure forgotten new theories born dissatisfaction status quo sincerely lotfi lotfi zadeh professor graduate school director berkeley initiative soft computing bisc address 729 soda hall 1776 computer science division department electrical engineering computer sciences university california berkeley ca 947201776 gzrdaeecsberkeleyedu teloffice 510 6424959 fax office 510 6421712 telhome 510 5262569 fax home 510 5262433 url httpwwwcsberkeleyeduzadeh bisc homepage urls url httpwwwbisccsberkeleyedu url httpzadehcsberkeleyedu _______________________________________________ uai mailing list faqengrorstedu httpssecureengroregonstateedumailmanlistinfouai richard e neapolitan professor chair computer science northeastern illinois university 5500 n st louis chicago illinois 60625 thu 07 aug 2008 054805 0600 uai determinism verses chance actually fuzzy