Fair Division Beyond Monotone Valuations with Applications to Equitable Graph Partitioning

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Authors: Siddharth Barman, Paritosh Verma
Cited by: 0

Abstract

This paper studies fair division of divisible and indivisible items among agents whose cardinal preferences are not necessarily monotone. We establish the existence of fair divisions and develop approximation algorithms to compute them. We address two complementary valuation classes, subadditive and nonnegative, which go beyond monotone functions. Considering both the division of cake (divisible resources) and allocation of indivisible items, we obtain fairness guarantees in terms of (approximate) envy-freeness (EF) and equability (EQ). In the context of envy-freeness, we prove that an EF division of a cake always exists under cake valuations that are subadditive and globally nonnegative (i.e., the value of the entire cake for every agent is nonnegative, but parts of the cake can be burnt). This result notably complements the nonexistence of EF allocations for burnt cakes known for more general valuations. For envy-freeness in the indivisible-items setting, we establish the existence of EFE3 allocations for subadditive and globally nonnegative valuations; again, such valuations can be non-monotone and can impart negative value to specific item subsets. In addition, we obtain universal existence of EFE3 allocations under nonnegative valuations. We study equitability under nonnegative valuations. Here, we prove that EQE3 allocations always exist when the agents’ valuations are nonnegative (and possibly non-monotone). Also, in the indivisible-items setting, we develop an approximation algorithm that, for given nonnegative valuations, finds allocations that are equitable within additive margins. Our results have combinatorial implications, which highlight the reach of the developed guarantees beyond fair division and even algorithmic game theory.

Fields of Study & Subjects

Game Theory and Voting Systems Auction Theory and Applications Ethics and Social Impacts of AI

Publication details

Journal / source
Society for Industrial and Applied Mathematics eBooks
Pages
6613–6641
Publication date
1 January 2026
Language
EN