| Description |
1 online resource (462 pages) |
| Series |
LNCS sublibrary. SL 7, Artificial intelligence |
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Lecture Notes in Computer Science ; 11940 |
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Lecture notes in artificial intelligence |
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LNCS sublibrary. SL 7, Artificial intelligence
|
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Lecture notes in computer science ; 11940
|
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Lecture notes in computer science. Lecture notes in artificial intelligence.
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| Contents |
Intro; Preface; Organization; Contents; An Experimental Study on the Behaviour of Inconsistency Measures; 1 Introduction; 2 Preliminaries; 3 Inconsistency Measures; 4 Experiments; 4.1 Knowledge Base Generation; 4.2 Evaluation Measures; 4.3 Results; 5 Conclusion; References; Inconsistency Measurement; 1 Introduction; 2 Preliminaries; 3 Measuring Inconsistency; 4 Approaches; 4.1 Measures Based on Minimal Inconsistent Sets; 4.2 Measures Based on Non-classical Semantics; 4.3 Further Measures; 5 Beyond Propositional Logic; 5.1 First-Order and Description Logic; 5.2 Probabilistic Logic |
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1 Introduction2 Background; 2.1 Belief Function and Credal Partition; 2.2 Evidential C-Means Algorithm; 2.3 Evidential Constrained C-Means Algorithm; 3 The LPECM Algorithm with Instance-Level Constraints; 3.1 Objective Function; 3.2 Optimization; 3.3 Metric Optimization; 4 Experiments; 4.1 Experimental Protocols; 4.2 Toy Data Set; 4.3 Real Data Sets; 5 Conclusion; References; Hybrid Reasoning on a Bipolar Argumentation Framework; 1 Introduction; 2 Bipolar Argumentation Framework; 3 Description of Legal Knowledge in a BAF; 4 Reasoning Using the BAF; 4.1 Outline; 4.2 Bottom-Up Reasoning |
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3 Decomposition of Causal Interaction Models4 Properties of a Cascading Representation; 4.1 The Cascading Representation and Its Equivalence Property; 4.2 Additional Engineering Benefits; 5 Conclusions and Further Research; References; Computational Models for Cumulative Prospect Theory: Application to the Knapsack Problem Under Risk; 1 Introduction; 2 Related Work; 3 CPT and Strong Risk Aversion; 4 A First Linearization for CPT Optimization; 5 The Case of Piecewise Linear Weighting Functions; 6 Conclusion; References; On a New Evidential C-Means Algorithm with Instance-Level Constraints |
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4.3 Top-Down Reasoning4.4 Hybrid Reasoning; 4.5 Correctness; 5 Related Works; 6 Conclusion; References; Active Preference Elicitation by Bayesian Updating on Optimality Polyhedra; 1 Introduction; 2 Background and Notations; 3 Incremental Elicitation Approach; 4 Experimental Results; 5 Conclusion; References; Selecting Relevant Association Rules From Imperfect Data; 1 Introduction; 2 Theoretical Background and Related Work; 2.1 Theoretical Background; 2.2 Problem Statement and Related Work; 3 Proposed Approach; 3.1 Assessing Rule Interestingness from Imprecise Data; 3.2 Search Space Reduction |
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5.3 Non-monotonic Logics6 Summary and Discussion; References; Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study; 1 Introduction; 2 Preliminaries; 2.1 Abstract Argumentation; 2.2 Artificial Neural Networks and Graph Convolutional Networks; 3 Casting the Acceptability Problem as a Classification Problem; 4 Experimental Evaluation; 4.1 Datasets; 4.2 Experimental Setup; 4.3 Results; 5 Conclusion; References; The Hidden Elegance of Causal Interaction Models; 1 Introduction; 2 Preliminaries |
| Summary |
This book constitutes the refereed proceedings of the 13th International Conference on Scalable Uncertainty Management, SUM 2019, which was held in Compiègne, France, in December 2019. The 25 full, 4 short, 4 tutorial, 2 invited keynote papers presented in this volume were carefully reviewed and selected from 44 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models |
| Notes |
3.3 Rules Selection Process |
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Includes author index |
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Print version record |
| Subject |
Uncertainty (Information theory) -- Congresses.
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Uncertainty (Information theory)
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| Genre/Form |
Conference papers and proceedings.
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| Form |
Electronic book
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| Author |
Ben Amor, Nahla.
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Quost, Benjamin.
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Theobald, Martin (Computer scientist)
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| ISBN |
3030355144 |
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9783030355142 |
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