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Algorithmic Decision Theory

4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings

  • Conference proceedings
  • © 2015

Overview

Editors:
  1. Toby Walsh

    1. University of New South Wales, Kensington, Australia

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  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9346)

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

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Conference proceedings info: ADT 2015.

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About this book

This book constitutes the thoroughly refereed conference proceedings of the 4th International Conference on Algorithmic Decision Theory , ADT 2015, held in September 2015 in Lexington, USA. The 32 full papers presented were carefully selected from 76 submissions. The papers are organized in topical sections such as preferences; manipulation, learning and other issues; utility and decision theory; argumentation; bribery and control; social choice; allocation and other problems; doctoral consortium.

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Table of contents (38 papers)

  1. Front Matter

    Pages I-XII
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  2. Preferences

    1. Front Matter

      Pages 1-1
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    2. Beyond Theory and Data in Preference Modeling: Bringing Humans into the Loop

      • Thomas E. Allen, Muye Chen, Judy Goldsmith, Nicholas Mattei, Anna Popova, Michel Regenwetter et al.
      Pages 3-18

    3. Reasoning with Preference Trees over Combinatorial Domains

      • Xudong Liu, Miroslaw Truszczynski
      Pages 19-34

    4. Group Activity Selection from Ordinal Preferences

      • Andreas Darmann
      Pages 35-51

    5. Towards Decision Making via Expressive Probabilistic Ontologies

      • Erman Acar, Camilo Thorne, Heiner Stuckenschmidt
      Pages 52-68

  3. Manipulation

    1. Front Matter

      Pages 69-69
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    2. Manipulation of k-Approval in Nearly Single-Peaked Electorates

      • Gábor Erdélyi, Martin Lackner, Andreas Pfandler
      Pages 71-85

    3. Manipulation and Bribery When Aggregating Ranked Preferences

      • Ying Zhu, Miroslaw Truszczynski
      Pages 86-102

    4. Complexity of Manipulative Actions When Voting with Ties

      • Zack Fitzsimmons, Edith Hemaspaandra
      Pages 103-119

  4. Learning and Other Issues

    1. Front Matter

      Pages 121-121
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    2. Bayesian Network Structure Learning with Messy Inputs: The Case of Multiple Incomplete Datasets and Expert Opinions

      • Shravan Sajja, Léa A. Deleris
      Pages 123-138

    3. Reducing the Number of Queries in Interactive Value Iteration

      • Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
      Pages 139-152

    4. Learning the Parameters of a Non Compensatory Sorting Model

      • Olivier Sobrie, Vincent Mousseau, Marc Pirlot
      Pages 153-170

    5. k-Agent Sufficiency for Multiagent Stochastic Physical Search Problems

      • Daniel S. Brown, Steven Loscalzo, Nathaniel Gemelli
      Pages 171-186

  5. Utility and Decision Theory

    1. Front Matter

      Pages 187-187
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    2. Geometry on the Utility Space

      • François Durand, Benoît Kloeckner, Fabien Mathieu, Ludovic Noirie
      Pages 189-204

    3. Sequential Extensions of Causal and Evidential Decision Theory

      • Tom Everitt, Jan Leike, Marcus Hutter
      Pages 205-221

    4. MOPIC Properties in the Representation of Preferences by a 2-Additive Choquet Integral

      • Brice Mayag
      Pages 222-235

    5. Profitable Deviation Strong Equilibria

      • Laurent Gourvès
      Pages 236-252
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  1. Algorithmic Decision Theory

Editors and Affiliations

  • University of New South Wales, Kensington, Australia

    Toby Walsh

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