Truth, Justice, and Cake Cutting
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CitationChen, 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.
AbstractCake 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.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:8896229
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