Judgment Aggregation

Judgment Aggregation

A Primer

Davide Grossi, Gabriella Pigozzi,
ISBN: 9781627050876 | PDF ISBN: 9781627050883
Copyright © 2015 | 151 Pages | Publication Date: 03/01/2014

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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.

Table of Contents

Logic Meets Social Choice Theory
Basic Concepts
Coping with Impossibility
Aggregation Rules
Authors' Biographies

About the Author(s)

Davide Grossi, University of Liverpool, UK
Davide Grossi is a Lecturer (Assistant Professor) at the Computer Science Department of the University of Liverpool (UK). He holds a master's degree cum laude in Philosophy from the Scuola Normale Superiore of Pisa (Italy) and a Ph.D. in Computer Science from Utrecht University (the Netherlands). His Ph.D. thesis was nominated for the Christiaan Huygens Prijs 2009 of the Royal Netherlands Academy of Arts and Sciences. Prior to joining the University of Liverpool, he worked as a postdoctoral researcher at the Computer Science and Communications Department of the University of Luxembourg (on a personal grant sponsored by the National Research Fund of Luxembourg) and at the Institute for Logic, Language, and Computation of the University of Amsterdam (on a personal grant sponsored by the Netherlands Organisation for Scientific Research). He is author of over 40 peer-reviewed articles in international journals and conferences in philosophy, logic, artificial intelligence and multi-agent systems. He regularly serves as reviewer for top journals and conferences in his areas of expertise.

Gabriella Pigozzi, Universite Paris Dauphine
Gabriella Pigozzi is an Associate Professor in Computer Science at Universite Paris Dauphine (France) and a member of the LAMSADE Lab. After a Ph.D. in Philosophy from the University of Genova (Italy), she held postdoc positions at the Center for Junior Research Fellows of the University of Konstanz (Germany), at the Computer Science Department of King's College London (on a personal postdoctoral fellowship sponsored by the Economic and Social Research Council), and at the Computer Science and Communications Department of the University of Luxembourg. She obtained grants from the Engineering and Physical Sciences Research Council (UK) and the National Agency for Research (France). Her research focuses on judgment aggregation, computational social choice, argumentation theory, and normative multi-agent systems. She published over 40 peer-reviewed articles in international conferences and journals.


Related Series

Human Language Technologies


Judgment aggregation is a relatively new theory and framework for studying collective decision making. Unlike social choice theory, which models collective decision by aggregation of preferences, judgment aggregation models it by aggregation of sets of judgments. Partly because of this generalization, judgment aggregation has attracted researchers from various fields since its very beginning, including logic, philosophy, computer science, economics, law, and political science. For better collaboration and mutual understanding from these different fields, it would be great if there were an accessible textbook as well as an up-to-date survey of the progress in judgment aggregation. This book has just provided the desiderata. Apart from the introduction of the basic theory of judgment aggregation, each chapter devotes a section to further topics and some also include open issues. This makes the book an excellent reference for beginners who are eager to dive into the frontiers of judgment aggregation. The book also merits intensive reading because it provides the most clear and accessible proofs of the main theorems in judgment aggregation, though some basic knowledge of propositional logic is assumed. Some hard and long proofs are presented with diagrams illustrating the logical structures of them, making the book very user-friendly. Moreover, the proof method of using (ultra)filters for the impossibility theorems is general enough to be adapted to prove other impossibility results.
Xuefeng Wen

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