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Titlebook: Algorithmic Decision Theory; First International Francesca Rossi,Alexis Tsoukias Conference proceedings 2009 Springer-Verlag Berlin Heidel

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期刊全称Algorithmic Decision Theory
期刊简称First International
影响因子2023Francesca Rossi,Alexis Tsoukias
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Algorithmic Decision Theory; First International  Francesca Rossi,Alexis Tsoukias Conference proceedings 2009 Springer-Verlag Berlin Heidel
影响因子This volume contains the papers presented at ADT 2009, the first International Conference on Algorithmic Decision Theory. The conference was held in San Servolo, a small island of the Venice lagoon, during October 20-23, 2009. The program of the conference included oral presentations, posters, invited talks, and tutorials. The conference received 65 submissions of which 39 papers were accepted (9 papers were posters). The topics of these papers range from computational social choice preference modeling, from uncertainty to preference learning, from multi-criteria decision making to game theory.
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Projective Dependency Structures,procedure and distance-based merging. The conclusion-based procedure has been little investigated because it provides a way to aggregate the conclusions, but not the premises, thus it outputs an incomplete judgment set. The goal of this paper is to present a conclusion-based procedure outputting complete judgment sets.
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Dependency or Interdependency in Old Agerepresentation of profiles and majority outcomes. Within this geometric framework, we show how profile decompositions can be used to derive restrictions on profiles that avoid the paradoxes of majority voting.
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https://doi.org/10.1007/978-94-010-1409-0games that need to be thrown to manipulate the result can also be determined in polynomial time. Finally, we show that there are several different variations of standard cup competitions where manipulation remains polynomial.
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Emma-Louise Anderson,Amy S. Pattersoninterpreted as anonymous non-discriminatory prices. Additionally, we study the canonical makespan-minimizing scheduling problem of unrelated machines, in an envy-free manner. For the special case of related machines model we show that tight algorithmic bounds can be achieved.
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Paolo Ghisletta,Eva Cantoni,Nadège Jacot problems, and ., being an outranking method applying robust ordinal regression to well known ELECTRE methods. In this way, we obtain corresponding methods for group decision: .-GROUP, .-GROUP and .-GROUP.
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