The learnability of voting rules
type: Item
instance of: scholarly article
title: The learnability of voting rules
zbMATH Open document ID: 1191.68524
author: Ariel D. Procaccia
author: Aviv Zohar
author: Yoni Peleg
author: Jeffrey S. Rosenschein
published in: Artificial Intelligence
publication date: 2009-09-14T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 91B12
zbMATH DE Number: 5603684
zbMATH Keywords: computational social choice
zbMATH Keywords: computational learning theory
zbMATH Keywords: multiagent systems
describes a project that uses: LPbook
MaRDI profile type: Publication
full work available at URL: j.artint.2009.03.003
OpenAlex ID: W2067594415
cites work: How hard is it to control an election?
cites work: When are elections with few candidates hard to manipulate?
cites work: Q3772828
cites work: Financial Cryptography and Data Security
cites work: A heuristic technique for multi-agent planning
cites work: A new perspective on implementation by voting trees
cites work: Q4198056
cites work: Dichotomy for voting systems
cites work: Anyone but him: the complexity of precluding an alternative
cites work: Learnability and rationality of choice.
cites work: Probably Approximate Learning of Sets and Functions
cites work: Q3624050
cites work: Sophisticated voting rules: The case of two tournaments
cites work: Linear programming. Foundations and extensions
cites work: Social Choice Scoring Functions
cites work: Q3579475
DOI: 10.1016/J.ARTINT.2009.03.003
description: scientific article; zbMATH DE number 5603684