Truth, Justice, and Cake Cutting

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.

Cite

Text

Chen et al. "Truth, Justice, and Cake Cutting." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7621

Markdown

[Chen et al. "Truth, Justice, and Cake Cutting." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/chen2010aaai-truth/) doi:10.1609/AAAI.V24I1.7621

BibTeX

@inproceedings{chen2010aaai-truth,
  title     = {{Truth, Justice, and Cake Cutting}},
  author    = {Chen, Yiling and Lai, John K. and Parkes, David C. and Procaccia, Ariel D.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2010},
  pages     = {756-761},
  doi       = {10.1609/AAAI.V24I1.7621},
  url       = {https://mlanthology.org/aaai/2010/chen2010aaai-truth/}
}