Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 13th European Conference, ECSQARU 2015, Compiègne, France, July 15-17, 2015. Proceedings (Lecture Notes in Computer Science (9161))

This book constitutes the refereed proceedings of the 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2015, held in Compiègne, France, in July 2015. The 49 revised full papers presented were carefully reviewed and selected from 69 submissions and cover topics on decision theory and preferences; argumentation; conditionals; game theory; belief update; classification; inconsistency; graphical models; Bayesian networks; belief functions; logic; and probabilistic graphical models for scalable data analytics. Papers come from researchers interested in advancing the technology and from practitioners using uncertainty techniques in real-world applications. The scope of the ECSQARU conferences encompasses fundamental issues, representation, inference, learning, and decision making in qualitative and numeric uncertainty paradigms. Front Matter....Pages I-XIII Front Matter....Pages 1-1 Minimizing Regret in Dynamic Decision Problems....Pages 3-13 Extracting Decision Rules from Qualitative Data Using Sugeno Integral: A Case-Study....Pages 14-24 Elicitation of a Utility from Uncertainty Equivalent Without Standard Gambles....Pages 25-35 Possibilistic Conditional Preference Networks....Pages 36-46 Front Matter....Pages 47-47 On Supported Inference and Extension Selection in Abstract Argumentation Frameworks....Pages 49-59 Representing and Reasoning About Arguments Mined from Texts and Dialogues....Pages 60-71 Dialogue Games for Argumentation Frameworks with Necessities....Pages 72-82 Explaining Bayesian Networks Using Argumentation....Pages 83-92 Front Matter....Pages 93-93 Transitive Reasoning with Imprecise Probabilities....Pages 95-105 On the Algebraic Structure of Conditional Events....Pages 106-116 In All, but Finitely Many, Possible Worlds: Model-Theoretic Investigations on ‘Overwhelming Majority’ Default Conditionals....Pages 117-126 Front Matter....Pages 127-127 The Robustness of Periodic Orchestrations in Uncertain Evolving Environments....Pages 129-140 Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance....Pages 141-150 Game-Theoretic Resource Allocation with Real-Time Probabilistic Surveillance Information....Pages 151-161 Front Matter....Pages 163-163 Belief Update Within Propositional Fragments....Pages 165-174 Private Expansion and Revision in Multi-agent Settings....Pages 175-185 Contraction in Propositional Logic....Pages 186-196 Front Matter....Pages 197-197 Multi-classifiers of Small Treewidth....Pages 199-209 Balanced Tuning of Multi-dimensional Bayesian Network Classifiers....Pages 210-220 A New View of Conformity and Its Application to Classification....Pages 221-232 Front Matter....Pages 233-233 Using Shapley Inconsistency Values for Distributed Information Systems with Uncertainty....Pages 235-245 Consistency-Based Reliability Assessment....Pages 246-256 Handling Revision Inconsistencies: Towards Better Explanations....Pages 257-266 On Measuring Inconsistency Using Maximal Consistent Sets....Pages 267-276 Front Matter....Pages 277-277 On the Analysis of Probability-Possibility Transformations: Changing Operations and Graphical Models....Pages 279-289 Computing Concise Representations of Semi-graphoid Independency Models....Pages 290-300 Learning Structure in Evidential Networks from Evidential DataBases....Pages 301-311 Evaluating Product-Based Possibilistic Networks Learning Algorithms....Pages 312-321 Front Matter....Pages 323-323 Every LWF and AMP Chain Graph Originates from a Set of Causal Models....Pages 325-334 Factorization, Inference and Parameter Learning in Discrete AMP Chain Graphs....Pages 335-345 A Differential Approach for Staged Trees....Pages 346-355 CPD Tree Learning Using Contexts as Background Knowledge....Pages 356-365 Relevance of Evidence in Bayesian Networks....Pages 366-375 Hybrid Time Bayesian Networks....Pages 376-386 Learning Bounded Tree-Width Bayesian Networks via Sampling....Pages 387-396 Learning Conditional Distributions Using Mixtures of Truncated Basis Functions....Pages 397-406 MPE Inference in Conditional Linear Gaussian Networks....Pages 407-416 Front Matter....Pages 417-417 Dynamic Time Warping Distance for Message Propagation Classification in Twitter....Pages 419-428 A Reliably Weighted Collaborative Filtering System....Pages 429-439 A Comparison of Plausibility Conflict and of Degree of Conflict Based on Amount of Uncertainty of Belief Functions....Pages 440-450 Front Matter....Pages 417-417 Weighted Maximum Likelihood for Parameters Learning Based on Noisy Labels in Discrete Hidden Markov Models....Pages 451-460 Evidential Editing K-Nearest Neighbor Classifier....Pages 461-471 Learning Contextual Discounting and Contextual Reinforcement from Labelled Data....Pages 472-481 Front Matter....Pages 483-483 Symbolic Possibilistic Logic: Completeness and Inference Methods....Pages 485-495 Probabilistic Common Knowledge Among Infinite Number of Agents....Pages 496-505 Towards Lifted Inference Under Maximum Entropy for Probabilistic Relational FO-PCL Knowledge Bases....Pages 506-516 Front Matter....Pages 517-517 Towards Gaussian Bayesian Network Fusion....Pages 519-528 Early Recognition of Maneuvers in Highway Traffic....Pages 529-540 Variable Elimination for Interval-Valued Influence Diagrams....Pages 541-551 Back Matter....Pages 553-554 This book constitutes the refereed proceedings of the 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2015, held in Compiegne, France, in July 2015.