Description 
1 online resource (462 pages) 
Series 
LNCS sublibrary. SL 7, Artificial intelligence 

Lecture Notes in Computer Science ; 11940 

Lecture notes in artificial intelligence 

LNCS sublibrary. SL 7, Artificial intelligence


Lecture notes in computer science ; 11940


Lecture notes in computer science. Lecture notes in artificial intelligence.

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 Nonclassical Semantics; 4.3 Further Measures; 5 Beyond Propositional Logic; 5.1 FirstOrder and Description Logic; 5.2 Probabilistic Logic 

1 Introduction2 Background; 2.1 Belief Function and Credal Partition; 2.2 Evidential CMeans Algorithm; 2.3 Evidential Constrained CMeans Algorithm; 3 The LPECM Algorithm with InstanceLevel 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 BottomUp Reasoning 

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 CMeans Algorithm with InstanceLevel Constraints 

4.3 TopDown 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 

5.3 Nonmonotonic 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 

Includes author index 

Print version record 
Subject 
Uncertainty (Information theory)  Congresses.


Uncertainty (Information theory)

Genre/Form 
Conference papers and proceedings.

Form 
Electronic book

Author 
Ben Amor, Nahla.


Quost, Benjamin.


Theobald, Martin (Computer scientist)

ISBN 
3030355144 

9783030355142 
