IJCAI 2023poster3 citations

Approximate Envy-Freeness in Graphical Cake Cutting

Sheung Man Yuen, Warut Suksompong

Abstract

We study the problem of fairly allocating a divisible resource in the form of a graph, also known as graphical cake cutting. Unlike for the canonical interval cake, a connected envy-free allocation is not guaranteed to exist for a graphical cake. We focus on the existence and computation of connected allocations with low envy. For general graphs, we show that there is always a 1/2-additive-envy-free allocation and, if the agents' valuations are identical, a (2+\epsilon)-multiplicative-envy-free allocation for any \epsilon > 0. In the case of star graphs, we obtain a multiplicative factor of 3+\epsilon for arbitrary valuations and 2 for identical valuations. We also derive guarantees when each agent can receive more than one connected piece. All of our results come with efficient algorithms for computing the respective allocations.

Game Theory and Economic Paradigms: GTEP: Fair divisionGame Theory and Economic Paradigms: GTEP: Computational social choice
BibTeX
@inproceedings{ijcai2023p326,
  title     = {Approximate Envy-Freeness in Graphical Cake Cutting},
  author    = {Yuen, Sheung Man and Suksompong, Warut},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {2923--2930},
  year      = {2023},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2023/326},
  url       = {https://doi.org/10.24963/ijcai.2023/326},
}
Approximate Envy-Freeness in Graphical Cake Cutting · IJCAI 2023