LEADER 00879cam0-2200313---450 001 990005828150403321 005 20241203094504.0 035 $a000582815 035 $aFED01000582815 035 $a(Aleph)000582815FED01 035 $a000582815 100 $a19990604d1995----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $a<>dicibile e l'indicibile$everso un'estetica semio-linguistica$fGianfranco Marrone 210 $aPalermo$cL'epos$dc1995 215 $a204 p.$d22 cm 225 1 $aSaperi e scritture$v3 610 0 $aEstetica 676 $a111.85 700 1$aMarrone,$bGianfranco$f<1959- >$0144727 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990005828150403321 952 $a111.85 MARG 001$b9311 DFM$fFLFBC 959 $aFLFBC 996 $aDicibile e l'indicibile$9567057 997 $aUNINA LEADER 04714nam 22006975 450 001 9910484125803321 005 20251226195926.0 024 7 $a10.1007/b107184 035 $a(CKB)1000000000212898 035 $a(SSID)ssj0000316974 035 $a(PQKBManifestationID)11237053 035 $a(PQKBTitleCode)TC0000316974 035 $a(PQKBWorkID)10287822 035 $a(PQKB)11229400 035 $a(DE-He213)978-3-540-32235-1 035 $a(MiAaPQ)EBC4976816 035 $a(MiAaPQ)EBC6700585 035 $a(Au-PeEL)EBL4976816 035 $a(CaONFJC)MIL140249 035 $a(OCoLC)1024281024 035 $a(Au-PeEL)EBL6700585 035 $a(PPN)123093317 035 $a(MiAaPQ)EBC5585461 035 $a(EXLCZ)991000000000212898 100 $a20100715d2005 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aConditionals, Information, and Inference $eInternational Workshop, WCII 2002, Hagen, Germany, May 13-15, 2002, Revised Selected Papers /$fedited by Gabriele Kern-Isberner, Wilhelm Rödder, Friedhelm Kulmann 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XII, 219 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3301 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-32235-3 311 08$a3-540-25332-7 320 $aIncludes bibliographical references and index. 327 $aInvited Papers -- What Is at Stake in the Controversy over Conditionals -- Reflections on Logic and Probability in the Context of Conditionals -- Acceptance, Conditionals, and Belief Revision -- Regular Papers -- Getting the Point of Conditionals: An Argumentative Approach to the Psychological Interpretation of Conditional Premises -- Projective Default Epistemology -- On the Logic of Iterated Non-prioritised Revision -- Assertions, Conditionals, and Defaults -- A Maple Package for Conditional Event Algebras -- Conditional Independences in Gaussian Vectors and Rings of Polynomials -- Looking at Probabilistic Conditionals from an Institutional Point of View -- There Is a Reason for Everything (Probably): On the Application of Maxent to Induction -- Completing Incomplete Bayesian Networks. 330 $aConditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false ? rather, a conditional ?if A then B? provides a context, A, for B to be plausible (or true) and must not be confused with ?A entails B? or with the material implication ?not A or B.? This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The ?rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti?cial Intelligence made claims for appropriate formaltoolstohandle?generalizedrules.?Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3301 606 $aArtificial intelligence 606 $aMachine theory 606 $aArtificial Intelligence 606 $aFormal Languages and Automata Theory 615 0$aArtificial intelligence. 615 0$aMachine theory. 615 14$aArtificial Intelligence. 615 24$aFormal Languages and Automata Theory. 676 $a511.352 702 $aRo?dder$b Wilhelm 702 $aKern-Isberner$b Gabriele$f1956- 702 $aKulmann$b Friedhelm 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484125803321 996 $aConditionals, Information, and Inference$9772476 997 $aUNINA