Publication:

Truth, Justice, and Cake Cutting

Thumbnail Image

Open/View Files

truth_justice_and_cake.pdf (154 KB)

Date

2010

Authors

Published Version

10.1016/j.geb.2012.10.009

Journal Title

Journal ISSN

Volume Title

Publisher

Association for the Advancement of Artificial Intelligence
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Chen, Yiling, John Kwang Lai, David C. Parkes, and Ariel D. Procaccia. 2010. Truth, justice, and cake cutting. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence and the Twenty-Second Innovative Applications of Artificial Intelligence Conference: 11-15 July, 2010, Atlanta, Georgia. Menlo Park, CA: AAAI Press.

Abstract

Cake cutting is a common metaphor for the division of a heterogeneous divisible good. There are numerous papers that study the problem of fairly dividing a cake; a small number of them also take into account self-interested agents and consequent strategic issues, but these papers focus on fairness and consider a strikingly weak notion of truthfulness. In this paper we investigate the problem of cutting a cake in a way that is truthful and fair, where for the first time our notion of dominant strategy truthfulness is the ubiquitous one in social choice and computer science. We design both deterministic and randomized cake cutting algorithms that are truthful and fair under different assumptions with respect to the valuation functions of the agents.

Description

Other Available Sources

Research Data

Keywords

Terms of Use

This article is made available under the terms and conditions applicable to Open Access Policy Articles (OAP), as set forth at Terms of Service

URI

http://nrs.harvard.edu/urn-3:HUL.InstRepos:8896229

Collections

FAS Scholarly Articles

Endorsement

Review

Supplemented By

Related Stories