Degrees of Guaranteed Envy-Freeness in Finite Bounded Cake-Cutting Protocols
Claudia Lindner, Joerg Rothe

TL;DR
This paper introduces a new measure called degree of guaranteed envy-freeness (DGEF) to evaluate finite bounded cake-cutting protocols and proposes a protocol with the highest known DGEF for any number of players, advancing fairness approximation.
Contribution
It defines DGEF as a new metric for assessing envy-freeness in finite protocols and presents a proportional protocol with optimal DGEF for all n ≥ 3.
Findings
Proposed a finite bounded proportional protocol with DGEF of 1 + ⌈ n^2/2 ⌉.
This protocol achieves the highest known DGEF among finite bounded protocols.
Improving DGEF beyond this level is identified as a significant challenge.
Abstract
Cake-cutting protocols aim at dividing a ``cake'' (i.e., a divisible resource) and assigning the resulting portions to several players in a way that each of the players feels to have received a ``fair'' amount of the cake. An important notion of fairness is envy-freeness: No player wishes to switch the portion of the cake received with another player's portion. Despite intense efforts in the past, it is still an open question whether there is a \emph{finite bounded} envy-free cake-cutting protocol for an arbitrary number of players, and even for four players. We introduce the notion of degree of guaranteed envy-freeness (DGEF) as a measure of how good a cake-cutting protocol can approximate the ideal of envy-freeness while keeping the protocol finite bounded (trading being disregarded). We propose a new finite bounded proportional protocol for any number n \geq 3 of players, and show…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimization and Search Problems · Caching and Content Delivery · Optimization and Packing Problems
