Judgment Aggregation. Gabriella Pigozzi

      

       Judgment Aggregation: A Primer

       Synthesis Lectures on Artificial Intelligence and Machine Learning

      Editors

       Ronald J. Brachman, Yahoo! Labs

       William W. Cohen, Carnegie Mellon University

       Peter Stone, University of Texas at Austin

      Judgment Aggregation: A Primer

      Davide Grossi and Gabriella Pigozzi

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      Copyright © 2014 by Morgan & Claypool

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.

      Judgment Aggregation: A Primer

      Davide Grossi and Gabriella Pigozzi

       www.morganclaypool.com

      ISBN: 9781627050876 paperback

      ISBN: 9781627050883 ebook

      DOI 10.2200/S00559ED1V01Y201312AIM027

      A Publication in the Morgan & Claypool Publishers series

       SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

      Lecture #27

      Series Editors: Ronald J. Brachman, Yahoo! Labs

      William W. Cohen, Carnegie Mellon University

      Peter Stone, University of Texas at Austin

      Series ISSN

      Synthesis Lectures on Artificial Intelligence and Machine Learning

      Print 1939-4608 Electronic 1939-4616

       Judgment Aggregation: A Primer

      Davide Grossi

      University of Liverpool

      Gabriella Pigozzi

      Université Paris Dauphine

       SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING #27

       ABSTRACT

      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,