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Record Nr. |
UNINA9910502665103321 |
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Titolo |
Symbolic and quantitative approaches to reasoning with uncertainty : 16th European conference, ECSQARU 2021, Prague, Czech Republic, September 21-24, 2021 : proceedings / / Jirrina Vejnarova, Nic Wilson (editors) |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2021] |
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©2021 |
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ISBN |
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Descrizione fisica |
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1 online resource (695 pages) |
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Collana |
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Lecture notes in computer science ; ; 12897 |
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Disciplina |
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Soggetti |
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Uncertainty (Information theory) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Intro -- Preface -- Organization -- Contents -- Argumentation and Analogical Reasoning -- Analogies Between Sentences: Theoretical Aspects - Preliminary Experiments -- 1 Introduction -- 2 Related Work -- 3 Formal Framework -- 3.1 Strong Analogical Proportions -- 3.2 Weak Analogical Proportions -- 3.3 Analogical Proportions and Implication -- 3.4 Analogical Proportions and Sentences -- 4 Experimental Context - Evaluation Metrics -- 4.1 Datasets -- 4.2 Embedding Techniques -- 4.3 Classifiers -- 5 Results -- 5.1 CNN and RF Results for Generated Sentences -- 5.2 CNN and RF Results for PDTB Dataset -- 6 Candidate Applications -- 7 Conclusion -- References -- Non-monotonic Explanation Functions -- 1 Introduction -- 2 Classification Problem -- 3 Abductive Explanation Functions -- 4 Properties of Explanation Functions -- 5 Argument-Based Explanation Function -- 6 Related Work -- 7 Conclusion -- References -- Similarity Measures Based on Compiled Arguments -- 1 Introduction -- 2 Background -- 2.1 Logical Concepts -- 2.2 Similarity Measures -- 3 Compilation of Arguments -- 4 Extended Similarity Measures -- 5 Extended Principles -- 6 Conclusion -- References -- Necessary and Sufficient Explanations for Argumentation-Based Conclusions -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 ASPIC+ -- 3.2 Basic Explanations -- 4 Necessity and Sufficiency -- 4.1 Necessity and |
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Sufficiency for Acceptance -- 4.2 Necessity and Sufficiency for Non-acceptance -- 4.3 Necessity, Sufficiency and Minimality -- 5 Applying Necessity and Sufficiency -- 6 Conclusion -- References -- Addressing Popular Concerns Regarding COVID-19 Vaccination with Natural Language Argumentation Dialogues -- 1 Introduction -- 2 Conceptualising Argumentation -- 2.1 Using Arguments and Concerns for a Persuasive Chatbot -- 2.2 Using an Argument Graph as Chatbot Knowledge Base -- 3 Hypotheses. |
4 Chatbot Design -- 4.1 Knowledge Base Construction -- 4.2 Understanding the User Input -- 5 Experiments -- 6 Evaluation of the Chatbot -- 7 Discussion and Conclusion -- References -- Argument Strength in Probabilistic Argumentation Using Confirmation Theory -- 1 Introduction -- 2 Defeasible Logic -- 3 Probabilistic Argumentation -- 4 Modelling Normality -- 5 Argument Strength -- 6 Confirmation Theory -- 7 Multiple Defeasible Rules -- 8 Discussion -- References -- The Degrees of Monotony-Dilemma in Abstract Argumentation -- 1 Introduction -- 2 Theoretical Preliminaries -- 3 Degrees of Monotony -- 4 The ``Degrees of Monotony''-Dilemma -- 5 Discussion -- 6 Conclusion -- References -- Constrained Incomplete Argumentation Frameworks -- 1 Introduction -- 2 Background -- 2.1 Dung's Abstract Argumentation -- 2.2 Incomplete AFs -- 3 Constrained IAFs -- 3.1 Constraints on Completions -- 3.2 Definition and Expressivity of CIAFs -- 3.3 Complexity Issues -- 4 CIAFs and Extension Enforcement -- 4.1 Expansion-Based Enforcement -- 4.2 Enforcement as Credulous Acceptability in CIAFs -- 5 Related Work -- 6 Conclusion -- References -- Complexity of Nonemptiness in Control Argumentation Frameworks -- 1 Introduction -- 2 Preliminaries -- 2.1 Abstract Argumentation Frameworks -- 2.2 Control Argumentation Frameworks -- 2.3 Some Background on Complexity Theory -- 3 Complexity of Nonemptiness in CAFs -- 4 Conclusion -- References -- Generalizing Complete Semantics to Bipolar Argumentation Frameworks -- 1 Introduction -- 2 Background -- 3 Bi-Complete Semantics -- 3.1 Expressiveness -- 3.2 Refinements -- 4 Related Work -- 5 Discussion -- References -- Philosophical Reflections on Argument Strength and Gradual Acceptability -- 1 Introduction -- 2 Background -- 2.1 Arguments as Statement or as Inferential Structures -- 2.2 Basic Concepts of Argument Structure and Relations. |
3 Logical, Dialectical and Rhetorical Argument Strength -- 4 Evaluating Semantics and Principles -- 4.1 Be Explicit About Which Aspects of Argument Strength Are Modelled -- 4.2 Be Explicit About the Interpretation of Arguments and Their Relations -- 5 Conclusion -- References -- An Abstract Argumentation and Logic Programming Comparison Based on 5-Valued Labellings -- 1 Introduction -- 2 Preliminaries -- 2.1 Abstract Argumentation -- 2.2 Logic Programs and Semantics -- 3 From Logic Programs to Argumentation Frameworks -- 3.1 Step 1: AF Instantiation -- 3.2 Step 2: Applying Argumentation Semantics -- 3.3 Step 3: Computing Conclusion Labellings -- 4 Semantic Correspondences -- 5 The L-Stable Semantics for Abstract Argumentation Frameworks -- 6 On the Role of Sink Arguments -- 7 Conclusion -- References -- Assumption-Based Argumentation Is Logic Programming with Projection -- 1 Introduction -- 2 Formal Preliminaries -- 2.1 Normal Logic Programs -- 2.2 Assumption-Based Argumentation -- 3 From ABA to LP -- 4 From LP to ABA -- 5 Summary and Main Result -- 6 Conclusion -- References -- A Paraconsistent Approach to Deal with Epistemic Inconsistencies in Argumentation -- 1 Introduction -- 2 The ASPIC? Framework -- 2.1 Attacks and Defeats -- 2.2 Abstract Argumentation Frameworks with Two Kinds of Defeats -- 3 Rationality Postulates -- 4 Related Work and Discussion -- 5 |
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Conclusion and Future Works -- References -- Gradual Semantics for Weighted Bipolar SETAFs -- 1 Introduction -- 2 Formal Setting -- 3 Desirable Properties -- 4 Links Between Properties -- 5 Gradual Semantics -- 6 Discussion -- References -- Bayesian Networks and Graphical Models -- Multi-task Transfer Learning for Bayesian Network Structures -- 1 Introduction -- 2 Bayesian Network Multi-task Structure Learning -- 3 The MT-MMHC Algorithm -- 3.1 Overall Process of MT-MMHC. |
3.2 The Combined Association Measure -- 3.3 MT Greedy Search with CPC Constraints -- 4 Experiments -- 4.1 Experimental Protocol -- 4.2 Empirical Results -- 5 Conclusion -- References -- Persuasive Contrastive Explanations for Bayesian Networks -- 1 Introduction -- 2 Persuasive Contrastive Explanations -- 3 Explanation Lattice -- 4 Computing Sufficient and Counterfactual Explanations -- 4.1 Searching the Lattice for Sufficient Explanations -- 4.2 Searching the Lattice for Counterfactual Explanations -- 4.3 Combining the Search for Explanations -- 4.4 Complexity and Further Optimisations -- 5 Related Work -- 6 Conclusions and Further Research -- References -- Explainable AI Using MAP-Independence -- 1 Introduction -- 2 Preliminaries and Notation -- 3 MAP-Independence -- 3.1 MAP-independence for Justification and Decision Support -- 4 Formal Problem Definition and Results -- 4.1 Computational Complexity -- 4.2 Algorithm and Algorithmic Complexity -- 5 Conclusion and Future Work -- References -- Bayesian Networks for the Test Score Prediction: A Case Study on a Math Graduation Exam -- 1 Introduction -- 2 Models -- 3 Probabilistic Inference -- 4 Efficient Inference Method for the Score Computation -- 5 Experimental Model Comparisons -- 6 Discussion -- References -- Fine-Tuning the Odds in Bayesian Networks -- 1 Introduction -- 2 Parametric Bayesian Networks -- 3 Parametric Markov Chains -- 4 Analysing Parametric BNs Using pMC Techniques -- 5 Experiments -- 6 Conclusion -- References -- Cautious Classification with Data Missing Not at Random Using Generative Random Forests -- 1 Introduction -- 2 Probabilistic Circuits and Generative Random Forests -- 3 Tractable Conservative Inference -- 4 Non-ignorable Training Data -- 5 Experiments -- 6 Conclusion -- References -- Belief Functions. |
Scoring Rules for Belief Functions and Imprecise Probabilities: A Comparison -- 1 Introduction -- 2 Dutch Books and Proper Scoring Rules -- 3 Background on Uncertainty Measures and Their Geometric Interpretation -- 4 Coherence for Belief Functions -- 5 Comparing Scoring Rules for Belief Functions and Imprecise Probabilities -- 5.1 Scoring Rule for Imprecise Probabilities -- 5.2 Distinguishing Belief Functions and Imprecise Probabilities Through Scoring Rules -- 6 Conclusion -- References -- Comparison of Shades and Hiddenness of Conflict -- 1 Introduction -- 2 Basic Notions -- 3 Hidden Conflict -- 4 Shades of Conflict -- 5 Comparison of both Approaches -- 5.1 Comparison by Examples -- 5.2 A Theoretic Comparison -- 6 Conclusion -- References -- Games of Incomplete Information: A Framework Based on Belief Functions -- 1 Introduction -- 2 Background and Motivations -- 2.1 Dempster-Shafer's Theory of Evidence -- 2.2 Decision Making with Belief Functions -- 2.3 Game Theory -- 3 Credal Games -- 4 From Credal Games to Complete Games -- 4.1 The Direct Transform -- 4.2 The Conditioned Transform -- 5 Conclusion -- References -- Uncertainty-Aware Resampling Method for Imbalanced Classification Using Evidence Theory -- 1 Introduction -- 2 Related Work -- 3 Theory of Evidence -- 4 Uncertainty-Aware Hybrid Re-Sampling Method (UAHS) -- 4.1 Creating Soft Labels -- 4.2 Cleaning the Majority Class -- 4.3 Applying Selective Minority |
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Oversampling -- 5 Experimental Study -- 5.1 Setup -- 5.2 Results Discussion -- 6 Conclusion -- References -- Approximations of Belief Functions Using Compositional Models -- 1 Motivation -- 2 Belief Functions -- 3 Compositional Models -- 4 Entropy -- 5 Example -- 6 Comparison of Heuristics on Random Models -- 7 Conclusions -- References -- Dempster-Shafer Approximations and Probabilistic Bounds in Statistical Matching -- 1 Introduction. |
2 Preliminaries. |
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