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Algorithmic Decision Theory

6th International Conference, ADT 2019, Durham, NC, USA, October 25–27, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Saša Pekeč

    1. Fuqua School of Business, Duke University, Durham, USA

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  2. Kristen Brent Venable

    1. Florida Institute for Human and Machine Cognition (IHMC), Pensacola, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11834)

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

Included in the following conference series:

Conference proceedings info: ADT 2019.

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Table of contents (10 papers)

  1. Front Matter

    Pages i-viii
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  2. Combining Local Search and Elicitation for Multi-Objective Combinatorial Optimization

    • Nawal Benabbou, Cassandre Leroy, Thibaut Lust, Patrice Perny
    Pages 1-16

  3. Robustness of Approval-Based Multiwinner Voting Rules

    • Grzegorz Gawron, Piotr Faliszewski
    Pages 17-31

  4. Towards Characterizing the Deterministic Combinatorial Constrained Efficient Space

    • Rica Gonen, Anat Lerner
    Pages 32-48

  5. Integrating Operators’ Preferences into Decisions of Unmanned Aerial Vehicles: Multi-layer Decision Engine and Incremental Preference Elicitation

    • Arwa Khannoussi, Alexandru-Liviu Olteanu, Christophe Labreuche, Pritesh Narayan, Catherine Dezan, Jean-Philippe Diguet et al.
    Pages 49-64

  6. Refugee Allocation in the Setting of Hedonic Games

    • Benno Kuckuck, Jörg Rothe, Anke Weißenfeld
    Pages 65-80

  7. Optimizing Social Welfare in Social Networks

    • Pascal Lange, Jörg Rothe
    Pages 81-96

  8. New Complexity Results on Aggregating Lexicographic Preference Trees Using Positional Scoring Rules

    • Xudong Liu, Miroslaw Truszczynski
    Pages 97-111

  9. On the Parameterized Complexity of Party Nominations

    • Neeldhara Misra
    Pages 112-125

  10. Gradient Methods for Solving Stackelberg Games

    • Roi Naveiro, David Ríos Insua
    Pages 126-140

  11. Interactive Elicitation of a Majority Rule Sorting Model with Maximum Margin Optimization

    • Ons Nefla, Meltem Öztürk, Paolo Viappiani, Imène Brigui-Chtioui
    Pages 141-157

  12. Back Matter

    Pages 159-181
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  1. Algorithmic Decision Theory

Keywords

About this book

This book constitutes the conference proceedings of the 6th International Conference on Algorithmic Decision Theory, ADT 2019, held in Durham, NC, USA, in October 2019.  The 10 full papers presented together with 7 short papers were carefully selected from 31 submissions. The papers focus on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of computer science, economics and operations research in order to improve the theory and practice of modern decision support.

Editors and Affiliations

  • Fuqua School of Business, Duke University, Durham, USA

    Saša Pekeč

  • Florida Institute for Human and Machine Cognition (IHMC), Pensacola, USA

    Kristen Brent Venable

Bibliographic Information

  • Book Title: Algorithmic Decision Theory

  • Book Subtitle: 6th International Conference, ADT 2019, Durham, NC, USA, October 25–27, 2019, Proceedings

  • Editors: Saša Pekeč, Kristen Brent Venable

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-31489-7

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-31488-0Published: 26 September 2019

  • eBook ISBN: 978-3-030-31489-7Published: 10 October 2019

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: VIII, 181

  • Number of Illustrations: 560 b/w illustrations, 18 illustrations in colour

  • Topics: Artificial Intelligence, Mathematics of Computing, Computer Applications

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