LEADER 01307nam2-2200409---450- 001 990001439400203316 005 20050610120329.0 035 $a000143940 035 $aUSA01000143940 035 $a(ALEPH)000143940USA01 035 $a000143940 100 $a20040219d1973----km-y0itay0103----ba 101 $aspa 102 $aGB 105 $a||||||||001yy 200 1 $a<> : Quarta parte de comedias, (Madrid 1672)$fPedro Calderon de la Barca 205 $arist. anast. 210 $aLondon$cGregg International Publishers Limited$d1973 215 $a563 p.$d22 cm 300 $aRipr. facs. dell'ed.: Madrid : por Ioseph Fernandez de Baendia, 1672 410 0$12001 454 1$12001 461 1$1001000143876$12001$aComedias 676 $a862.3 700 1$aCALDERÓN DE LA BARCA,$bPedro$0433597 801 0$aIT$bsalbc$gISBD 912 $a990001439400203316 951 $aVI.5.A. 134/10(II sp A 95/10)$b154 L.M.$cII sp 959 $aBK 969 $aUMA 979 $aSIAV6$b10$c20040219$lUSA01$h1424 979 $aSIAV6$b10$c20040219$lUSA01$h1425 979 $aPATRY$b90$c20040406$lUSA01$h1741 979 $aCOPAT1$b90$c20050610$lUSA01$h1203 979 $aFIORELLA$b90$c20070111$lUSA01$h1131 996 $aQuarta parte de comedias, (Madrid 1672$9935788 997 $aUNISA LEADER 05477nam 2200589Ia 450 001 9910782274603321 005 20230721032709.0 010 $a1-281-93816-5 010 $a9786611938161 010 $a981-277-984-1 035 $a(CKB)1000000000538138 035 $a(OCoLC)560635834 035 $a(CaPaEBR)ebrary10255442 035 $a(SSID)ssj0000157509 035 $a(PQKBManifestationID)11179233 035 $a(PQKBTitleCode)TC0000157509 035 $a(PQKBWorkID)10138913 035 $a(PQKB)11696215 035 $a(MiAaPQ)EBC1681341 035 $a(WSP)00001870 035 $a(Au-PeEL)EBL1681341 035 $a(CaPaEBR)ebr10255442 035 $a(CaONFJC)MIL193816 035 $a(OCoLC)815752883 035 $a(EXLCZ)991000000000538138 100 $a20080116d2008 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFoundations of decision-making agents$b[electronic resource] $elogic, probability and modality /$fSubrata Das 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific ;$a[London] $cImperial College Press$dc2008 215 $a1 online resource (385 p.) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a981-277-983-3 320 $aIncludes bibliographical references (p. 347-353) and index. 327 $ach. 1. Modeling agent epistemic states: an informal overview. 1.1. Models of agent epistemic states. 1.2. Propositional epistemic model. 1.3. Probabilistic epistemic model. 1.4. Possible world epistemic model. 1.5. Comparisons of models. 1.6. P3 model for decision-making agents -- ch. 2. Mathematical preliminaries. 2.1. Usage of symbols. 2.2. Sets, relations, and functions. 2.3. Graphs and trees. 2.4. Probability. 2.5. Algorithmic complexity -- ch. 3. Classical logics for the propositional epistemic model. 3.1. Propositional logic. 3.2. First-order logic. 3.3. Theorem proving procedure. 3.4. Resolution theorem proving. 3.5. Refutation procedure. 3.6. Complexity analysis -- ch. 4. Logic programming. 4.1. The concept. 4.2. Program clauses and goals. 4.3. Program semantics. 4.4. Definite programs. 4.5. Normal programs. 4.6. Prolog. 4.7. Prolog systems. 4.8. Complexity analysis -- ch. 5. Logical rules for making decisions. 5.1. Evolution of rules. 5.2. Bayesian probability theory for handling uncertainty. 5.3. Dempster-Shafer theory for handling uncertainty. 5.4. Measuring consensus. 5.5. Combining sources of varying confidence. 5.6. Advantages and disadvantages of rule-based systems -- ch. 6. Bayesian belief networks. 6.1. Bayesian belief networks. 6.2. Conditional independence in belief networks. 6.3. Evidence, belief, and likelihood. 6.4. Prior probabilities in networks without evidence. 6.5. Belief revision. 6.6. Evidence propagation in polytrees. 6.7. Evidence propagation in directed acyclic graphs. 6.8. Complexity of inference algorithms. 6.9. Acquisition of probabilities. 6.10. Advantages and disadvantages of belief networks. 6.11. Belief network tools -- ch. 7. Influence diagrams for making decisions. 7.1. Expected utility theory and decision trees. 7.2. Influence diagrams. 7.3. Inferencing in influence diagrams. 7.4. Compilation of influence diagrams. 7.5. Inferencing in strong junction tress -- ch. 8. Modal logics for the possible world epistemic model. 8.1. Historical development of modal logics. 8.2. Systems of modal logic. 8.3. Deductions in modal systems. 8.4. Modality. 8.5. Decidability and matrix method. 8.6. Relationships among modal systems. 8.7. Possible world semantics. 8.8. Soundness and completeness results. 8.9. Complexity and decidability of modal systems. 8.10. Modal first-order logics. 8.11. Resolution in modal first-order logics. 8.12. Modal epistemic logics. 8.13. Logic of agents beliefs (LAB) -- ch. 9. Symbolic argumentation for decision-making. 9.1. Toulmin's model of argumentation. 9.2. Domino decision-making model for P3. 9.3. Knowledge representation syntax of P3. 9.4. Formalization of P3 via LAB. 9.5. Aggregation via Dempster-Shafer theory. 9.6. Aggregation via Bayesian belief networks. 330 $aThis self-contained book provides three fundamental and generic approaches (logical, probabilistic, and modal) to representing and reasoning with agent epistemic states, specifically in the context of decision making. Each of these approaches can be applied to the construction of intelligent software agents for making decisions, thereby creating computational foundations for decision-making agents. In addition, the book introduces a formal integration of the three approaches into a single unified approach that combines the advantages of all the approaches. Finally, the symbolic argumentation approach to decision making developed in this book, combining logic and probability, offers several advantages over the traditional approach to decision making which is based on simple rule-based expert systems or expected utility theory. 606 $aIntelligent agents (Computer software) 606 $aArtificial intelligence$xComputer programs 615 0$aIntelligent agents (Computer software) 615 0$aArtificial intelligence$xComputer programs. 676 $a006.33 700 $aDas$b Subrata Kumar$01495495 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910782274603321 996 $aFoundations of decision-making agents$93719582 997 $aUNINA LEADER 05727nam 2200805Ia 450 001 9910958320003321 005 20200520144314.0 010 $a9786612156847 010 $a9781282156845 010 $a1282156845 010 $a9789027294562 010 $a9027294569 010 $a9781423761013 010 $a1423761014 024 7 $a10.1075/sfsl.54 035 $a(CKB)1000000000032343 035 $a(SSID)ssj0000199844 035 $a(PQKBManifestationID)12058783 035 $a(PQKBTitleCode)TC0000199844 035 $a(PQKBWorkID)10208857 035 $a(PQKB)11636327 035 $a(SSID)ssj0000281827 035 $a(PQKBManifestationID)12083124 035 $a(PQKBTitleCode)TC0000281827 035 $a(PQKBWorkID)10306750 035 $a(PQKB)20562265 035 $a(MiAaPQ)EBC622823 035 $a(Au-PeEL)EBL622823 035 $a(CaPaEBR)ebr10077291 035 $a(CaONFJC)MIL215684 035 $a(OCoLC)705531321 035 $a(DE-B1597)720676 035 $a(DE-B1597)9789027294562 035 $a(EXLCZ)991000000000032343 100 $a20050204d2005 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMeaning predictability in word formation $enovel, context-free naming units /$fPavol Stekauer 205 $a1st ed. 210 $aAmsterdam ;$aPhiladelphia $cJ. Benjamins Pub.$d2005 215 $axxii, 288 p 225 1 $aStudies in functional and structural linguistics,$x0165-7712 ;$vv. 54 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9789027215635 311 08$a9027215634 311 08$a9781588116338 311 08$a1588116336 320 $aIncludes bibliographical references and index. 327 $aMeaning Predictability in Word Formation -- Editorial page -- Title page -- LCC data -- Table of contents -- Acknowledgements -- List of abbreviations -- Introduction -- 1. Literature survey -- 1.1. General -- 1.2. The morphological tradition -- 1.2.1. Lees -- 1.2.2. Levi -- 1.2.3. Van Lint -- 1.2.4. Zimmer -- 1.2.5. Downing -- 1.2.6. Allen -- 1.3. Basic psycholinguistic models -- 1.3.1. Slot-filling models -- 1.3.2. Relation models -- 1.3.3. Analogy-based models -- 1.3.4. Combined and other models -- 1.3.5. Non-compound interpretation models -- 1.4. Summary -- 2. General word formation framework -- 2.1. An onomasiological model of word formation -- 2.2. Onomasiological Types -- 3. A theory of predictability -- 3.1. Why context-free meaning predictability? -- 3.2. Predictability - lexical meaning - conceptualisation - extra-linguistic knowledge -- 3.3. Predictability and the native/non-native speaker factor -- 3.4. Predictability and seme level -- 3.5. The meaning-prediction process -- 3.5.1. Predictability and the Onomasiological Type -- 3.6. Onomasiological Structure Rules -- 3.7. Predictability and productivity -- 3.8. Predictability and typicality -- 3.9. Predictability Rate -- 3.10. Objectified Predictability Rate -- 3.11. Hypotheses -- 4. The Experiments -- 4.1. Method -- 4.2. Experiment 1 -- 4.2.1. Sample naming units -- 4.2.2. Experimental data and their analysis -- 4.2.3. Summary 1 -- 4.3. Experiment 2 -- 4.3.1. Sample naming units -- 4.3.2. Experimental data and their analysis -- 4.3.3. Summary 2 -- 4.4. Experiment 3 -- 4.4.1. Sample naming units -- 4.4.2. Experimental data and their analysis -- 4.4.3. Summary 3 -- 4.5. Experiment 4 -- 4.5.1. Sample naming units -- 4.5.2. Experimental data and their analysis -- 4.5.3. Discussion -- 4.5.4. Summary 4. 327 $a4.6. Meaning predictability and associative meaning: The experimental results in the light of free association of words -- 4.6.1. Meaning predictability of conversions and the associative principle -- 4.6.2. Summary 5 -- 4.6.3. Meaning predictability of two-constituent naming units and the associative principle -- 4.6.4. Summary 6 -- 5. Conclusions -- 5.1. General -- 5.2. Conclusions -- Notes -- References -- Author index -- Subject index -- The series Studies In Functional And Structural Linguistics. 330 $aThis book aims to contribute to a growing interest amongst psycholinguists and morphologists in the mechanisms of meaning predictability. It presents a brand-new model of the meaning-prediction of novel, context-free naming units, relating the wordformation and wordinterpretation processes. Unlike previous studies, mostly focussed on N+N compounds, the scope of this book is much wider. It not only covers all types of complex words, but also discusses a whole range of predictability-boosting and -reducing conditions. Two measures are introduced, the Predictability Rate and the Objectified Predictability Rate, in order to compare the strength of predictable readings both within a word and relative to the most predictable readings of other coinages. Four extensive experiments indicate inter alia the equal predicting capacity of native and non-native speakers, the close interconnection between linguistic and extra-linguistic factors, the important role of prototypical semes, and the usual dominance of a single central reading. 410 0$aStudies in functional and structural linguistics ;$vv. 54. 606 $aGrammar, Comparative and general$xWord formation 606 $aSemantics 606 $aOnomasiology 615 0$aGrammar, Comparative and general$xWord formation. 615 0$aSemantics. 615 0$aOnomasiology. 676 $a401/.43 700 $aStekauer$b Pavol$0742387 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910958320003321 996 $aMeaning predictability in word formation$94346066 997 $aUNINA