Skip to main content
Springer Nature Link
Log in

Scalable Uncertainty Management

15th International Conference, SUM 2022, Paris, France, October 17–19, 2022, Proceedings

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Florence Dupin de Saint-Cyr

    1. IRIT-Université Toulouse, Toulouse, France

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Meltem Öztürk-Escoffier

    1. Université Paris-Dauphine - PSL, Paris, France

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Nico Potyka

    1. Imperial College London, London, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13562)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: SUM 2022.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

This book constitutes the refereed proceedings of the 15th International Conference on Scalable Uncertainty Management, SUM 2022, which was held in Paris, France, in October 2022.

The 19 full and 4 short papers presented in this volume were carefully reviewed and selected from 25 submissions. Besides that, the book also contains 3 abstracts of invited talks and 2 tutorial papers. The conference aims to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as artificial intelligence and machine learning, databases, information retrieval and data mining, the semantic web and risk analysis.

The chapter "Defining and Enforcing Descriptive Accuracy in Explanations: the Case of Probabilistic Classifiers" is licensed under the terms of the Creative Commons Attribution 4.0 International License.

Similar content being viewed by others

Keywords

Table of contents (25 papers)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  3. Full Papers: Non-classical Reasoning

    1. Front Matter

      Pages 35-35
      Download chapter PDF

    2. Towards a Principle-Based Approach for Case-Based Reasoning

      • Leila Amgoud, Vivien Beuselinck
      Pages 37-46

    3. Iterated Conditionals, Trivalent Logics, and Conditional Random Quantities

      • Lydia Castronovo, Giuseppe Sanfilippo
      Pages 47-63

    4. Using Atomic Bounds to Get Sub-modular Approximations

      • Sébastien Destercke, Agnes Rico, Olivier Strauss
      Pages 64-78

    5. Characterizing Multipreference Closure with System W

      • Jonas Haldimann, Christoph Beierle
      Pages 79-91

    6. From Forgetting Signature Elements to Forgetting Formulas in Epistemic States

      • Kai Sauerwald, Gabriele Kern-Isberner, Alexander Becker, Christoph Beierle
      Pages 92-106

  4. Full Papers: Inconsistency

    1. Front Matter

      Pages 107-107
      Download chapter PDF

    2. A Capacity-Based Semantics for Inconsistency-Tolerant Inferences

      • Didier Dubois, Henri Prade
      Pages 109-123

    3. An Approach to Inconsistency-Tolerant Reasoning About Probability Based on Łukasiewicz Logic

      • Tommaso Flaminio, Lluis Godo, Sara Ugolini
      Pages 124-138

    4. A Comparison of ASP-Based and SAT-Based Algorithms for the Contension Inconsistency Measure

      • Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm
      Pages 139-153

  5. Full Papers: Decision Making and Social Choice

    1. Front Matter

      Pages 155-155
      Download chapter PDF

    2. A Non-utilitarian Discrete Choice Model for Preference Aggregation

      • Martin Durand, Fanny Pascual, Olivier Spanjaard
      Pages 157-171

    3. Selecting the Most Relevant Elements from a Ranking over Sets

      • Sébastien Konieczny, Stefano Moretti, Ariane Ravier, Paolo Viappiani
      Pages 172-185

    4. Decision Making Under Severe Uncertainty on a Budget

      • Nawapon Nakharutai, Sébastien Destercke, Matthias C. M. Troffaes
      Pages 186-201

    5. An Improvement of Random Node Generator for the Uniform Generation of Capacities

      • Peiqi Sun, Michel Grabisch, Christophe Labreuche
      Pages 202-216

  6. Full Papers: Learning

    1. Front Matter

      Pages 217-217
      Download chapter PDF
Back to top

Other volumes

  1. Scalable Uncertainty Management

Editors and Affiliations

  • IRIT-Université Toulouse, Toulouse, France

    Florence Dupin de Saint-Cyr

  • Université Paris-Dauphine - PSL, Paris, France

    Meltem Öztürk-Escoffier

  • Imperial College London, London, UK

    Nico Potyka

Bibliographic Information

  • Book Title: Scalable Uncertainty Management

  • Book Subtitle: 15th International Conference, SUM 2022, Paris, France, October 17–19, 2022, Proceedings

  • Editors: Florence Dupin de Saint-Cyr, Meltem Öztürk-Escoffier, Nico Potyka

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-18843-5

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Softcover ISBN: 978-3-031-18842-8Published: 15 October 2022

  • eBook ISBN: 978-3-031-18843-5Published: 14 October 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVII, 371

  • Number of Illustrations: 18 b/w illustrations, 19 illustrations in colour

  • Topics: Artificial Intelligence

Publish with us

Policies and ethics

Back to top