Invited Talk 1
(Zoran Ognjanović, session chair)
- • Lluís Godo - Boolean Algebras of Conditionals,Probability and Logic
Invited Talk 2
(Gabriele Kern-Isberner, session chair)
- • Fabio Gagliardi Cozman - Knowledge Representation in Knowledge-Enhanced Machine Learning: How? Where?
Invited Talk 3
(Anthony Hunter, session chair)
- • Francesca Toni - Dialectical Explanations
Session 1 : Conditional, Default and Analogical Reasoning 1
(Laura Giordano, session chair)
- • Nelly Barbot, Laurent Miclet, Henri Prade, and Gilles Richard - A New Perspective on Analogical Proportions
- • Christoph Beierle and Steven Kutsch - On the Antecedent Normal Form of Conditional Knowledge Bases
- • Nahla Ben Amor, Didier Dubois, Henri Prade, and Syrine Saidi - Revisiting Conditional Preferences: From Defaults to Graphical Representations
- • Angelo Gilio and Giuseppe Sanfilippo - Conjunction of Conditional Events and t-Norms
Session 2: Conditional, Default and Analogical Reasoning 2
(LLuis Godo, session chair)
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• Laura Giordano and Valentina Gliozzi - Reasoning About Exceptions in Ontologies: An Approximation of the Multipreference Semantics
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• Steven Kutsch and Christoph Beierle - Computation of Closures of Nonmonotonic Inference Relations Induced by Conditional Knowledge Bases
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• Suryani Lim, Henri Prade, and Gilles Richard - Solving Word Analogies: A Machine Learning Perspective
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• Kai Sauerwald and Christoph Beierle - Decrement Operators in Belief Change
Session 3: Learning and Decision Making 1
(Jonathan Lawry, session chair)
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• Andrey Ruschel, Arthur Colombini Gusmão, Gustavo Padilha Polleti, and Fabio Gagliardi Cozman - Explaining Completions Produced by Embeddings of Knowledge Graphs
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• Zhourong Chen, Xiaopeng Li, Zhiliang Tian, and Nevin L. Zhang - Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion
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• İpek Kıvanç and Demet Özgür-Ünlüakın - An Effective Maintenance Policy for a Multi-component Dynamic System Using Factored POMDPs
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• Peixian Chen, Zhourong Chen, and Nevin L. Zhang - A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models
Session 4: Uncertain Reasoning for Applications
(Radim Jirousek, session chair)
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• Bojan Marinković, Paola Glavan, Zoran Ognjanović, Dragan Doder, and Thomas Studer - Probabilistic Consensus of the Blockchain Protocol
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• Jorge Castro, Joaquim Gabarro, and Maria Serna - Measuring Investment Opportunities Under Uncertainty
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• Federico Toffano and Nic Wilson - Balancing Schedules Using Maximum Leximin
Session 5: Learning and Decision Making 2
(Fabio Gagliardi Cozman, session chair)
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• Jonathan Lawry, Michael Crosscombe, and David Harvey - Epistemic Sets Applied to Best-of-n Problems
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• Mathilde Monvoisin and Philippe Leray - Multi-task Transfer Learning for Timescale Graphical Event Models
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• Thijs van Ommen, Wouter M. Koolen, and Peter D. Grünwald - Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness
Session 6: Belief functions
(Henri Prade, session chair)
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• Safa Ben Ayed, Zied Elouedi, and Eric Lefevre - Toward the Evaluation of Case Base Maintenance Policies Under the Belief Function Theory
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• Milan Daniel and Václav Kratochvíl - Belief Functions and Degrees of Non-conflictness
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• Radim Jiroušek and Václav Kratochvíl - On Expected Utility Under Ambiguity
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• Joaquín Abellán, Serafín Moral-García, and María Dolores Benítez - Combination in Dempster-Shafer Theory Based on a Disagreement Factor Between Evidences
Session 7: Argumentation 1
(Chiaki Sakama, session chair)
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• Leila Amgoud, Victor David, and Dragan Doder - Similarity Measures Between Arguments Revisited
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• Rihab Bouslama, Raouia Ayachi, and Nahla Ben Amor - A New Generic Framework for Mediated Multilateral Argumentation-Based Negotiation Using Case-Based Reasoning
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• Jérôme Delobelle and Serena Villata - Interpretability of Gradual Semantics in Abstract Argumentation
Session 8: Precise and Imprecise Probabilities 1
(Giuseppe Sanfilippo, session chair)
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• Jose M. Puerta, Juan A. Aledo, José A. Gámez, and Jorge D. Laborda - Structural Fusion/Aggregation of Bayesian Networks via Greedy Equivalence Search Learning Algorithm
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• Juan Carlos Alfaro, Enrique González Rodrigo, Juan Ángel Aledo, and José Antonio Gámez - A Probabilistic Graphical Model-Based Approach for the Label Ranking Problem
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• Stefano Bonzio, Tommaso Flaminio, and Paolo Galeazzi - Sure-Wins Under Coherence: A Geometrical Perspective
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• Andrey G. Bronevich and Igor N. Rozenberg - Conditioning of Imprecise Probabilities Based on Generalized Credal Sets
Session 9: Argumentation 2
(Nico Potyka, session chair)
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• Mariela Morveli-Espinoza, Juan Carlos Nieves, and Cesar Augusto Tacla - An Imprecise Probability Approach for Abstract Argumentation Based on Credal Sets
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• Anthony Hunter and Sylwia Polberg - A Model-Based Theorem Prover for Epistemic Graphs for Argumentation
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• Atefeh Keshavarzi Zafarghandi, Rineke Verbrugge, and Bart Verheij - Discussion Games for Preferred Semantics of Abstract Dialectical Frameworks
Session 10: Precise and Imprecise Probabilities 2
(Milan Studeny, session chair)
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• Šejla Dautović and Dragan Doder - Probabilistic Logic for Reasoning About Actions in Time
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• Tommaso Flaminio - Towards a Standard Completeness for a Probabilistic Logic on Infinite-Valued Events
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• Niki Pfeifer and Giuseppe Sanfilippo - Probability Propagation in Selected Aristotelian Syllogisms
Session 11: Argumentation 3
(Francesca Toni, session chair)
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• Nico Potyka, Sylwia Polberg, and Anthony Hunter - Polynomial-Time Updates of Epistemic States in a Fragment of Probabilistic Epistemic Argumentation
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• Chiaki Sakama and Katsumi Inoue - Ordering Argumentation Frameworks
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• Remi Wieten, Floris Bex, Henry Prakken, and Silja Renooij - Constructing Bayesian Network Graphs from Labeled Arguments
Session 12: Precise and Imprecise Probabilities 3
(Tommaso Flaminio, session chair)
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• Hamzeh Mohammadi and Thomas Studer - Bayesian Confirmation and Justifications
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• Milan Studený, Václav Kratochvíl, and Jiří Vomlel - On Irreducible Min-Balanced Set Systems
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• Natan T’Joens, Thomas Krak, Jasper De Bock, and Gert de Cooman - A Recursive Algorithm for Computing Inferences in Imprecise Markov Chains