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Generalized scoring rules: a framework that reconciles Borda and Condorcet

Generalized scoring rules: a framework that reconciles Borda and Condorcet Generalized Scoring Rules: A Framework That Reconciles Borda and Condorcet LIRONG XIA Harvard University Generalized scoring rules [Xia and Conitzer 08] are a relatively new class of social choice mechanisms. In this paper, we survey developments in generalized scoring rules, showing that they provide a fruitful framework to obtain general results, and also reconcile the Borda approach and Condorcet approach via a new social choice axiom. We comment on some high-level ideas behind GSRs and their connection to Machine Learning, and point out some ongoing work and future directions. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and Behavioral Sciences--Economics; I.2.11 [Distributed Artificial Intelligence]: Multiagent Systems General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Computational social choice, generalized scoring rules 1. INTRODUCTION Social choice theory focuses on developing principles and methods for representation and aggregation of individual ordinal preferences. Perhaps the most well-known application of social choice theory is political elections. Over centuries, many social choice mechanisms have been proposed and analyzed in the context of elections, where each agent (voter) uses a linear order over the alternatives (candidates) to represent her preferences (her vote). For historical reasons, we will use voting rules to denote social http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Generalized scoring rules: a framework that reconciles Borda and Condorcet

ACM SIGecom Exchanges , Volume 12 (1) – Jun 1, 2013

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/2509013.2509020
Publisher site
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Abstract

Generalized Scoring Rules: A Framework That Reconciles Borda and Condorcet LIRONG XIA Harvard University Generalized scoring rules [Xia and Conitzer 08] are a relatively new class of social choice mechanisms. In this paper, we survey developments in generalized scoring rules, showing that they provide a fruitful framework to obtain general results, and also reconcile the Borda approach and Condorcet approach via a new social choice axiom. We comment on some high-level ideas behind GSRs and their connection to Machine Learning, and point out some ongoing work and future directions. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and Behavioral Sciences--Economics; I.2.11 [Distributed Artificial Intelligence]: Multiagent Systems General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Computational social choice, generalized scoring rules 1. INTRODUCTION Social choice theory focuses on developing principles and methods for representation and aggregation of individual ordinal preferences. Perhaps the most well-known application of social choice theory is political elections. Over centuries, many social choice mechanisms have been proposed and analyzed in the context of elections, where each agent (voter) uses a linear order over the alternatives (candidates) to represent her preferences (her vote). For historical reasons, we will use voting rules to denote social

Journal

ACM SIGecom ExchangesAssociation for Computing Machinery

Published: Jun 1, 2013

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