Judgment aggregation : a primer
著者
書誌事項
Judgment aggregation : a primer
（Synthesis lectures on artificial intelligence and machine learning, #27）
Morgan & Claypool, c2014
- : pbk
大学図書館所蔵 全3件
注記
Including bibliographical references (p. 111- 127) and index
Series title on cover spelled "synthesis lectures on artifical intelligence and machine learning" in error.
内容説明・目次
内容説明
Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it.
目次
Preface
Acknowledgments
Logic Meets Social Choice Theory
Basic Concepts
Impossibility
Coping with Impossibility
Manipulability
Aggregation Rules
Deliberation
Bibliography
Authors' Biographies
Index
「Nielsen BookData」 より