Truth, Justice, and Cake Cutting

DSpace/Manakin Repository

Truth, Justice, and Cake Cutting

Citable link to this page

. . . . . .

Title: Truth, Justice, and Cake Cutting
Author: Chen, Yiling; Lai, John Kwang; Parkes, David C.; Procaccia, Ariel D.

Note: Order does not necessarily reflect citation order of authors.

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.
Full Text & Related Files:
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.
Published Version: http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/viewFile/1761/2083
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:8896229

Show full Dublin Core record

This item appears in the following Collection(s)

  • FAS Scholarly Articles [7362]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

Search DASH


Advanced Search
 
 

Submitters