Strategy-proof cake cutting mechanisms for all-or-nothing utility

Takamasa Ihara, Shunsuke Tsuruta, Taiki Todo, Yuko Sakurai, Makoto Yokoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


The cake cutting problem must fairly allocate a divisible good among agents who have varying preferences over it. Recently, designing strategy-proof cake cutting mechanisms has caught considerable attention from AI and MAS researchers. Previous works assumed that an agent’s utility function is additive so that theoretical analysis becomes tractable. However, in practice, agents have non-additive utility functions over a resource. In this paper, we consider the allor-nothing utility function as a representative example of non-additive utility because it can widely cover agents’ preferences for real-world resources, such as the usage of meeting rooms, time slots for computational resources, bandwidth usage, and so on. We first show the incompatibility between envy-freeness and Pareto efficiency when each agent has all-or-nothing utility. We next propose two strategy-proof mechanisms that satisfy Pareto efficiency, which are based on a serial dictatorship mechanism, at the sacrifice of envy-freeness. To address computational feasibility, we propose an approximation algorithm to find a near-optimal allocation in time polynomial in the number of agents, since the problem of finding a Pareto efficient allocation is NP-hard. As another approach that abandon Pareto efficiency, we develop an envy-free mechanism and show that one of our serial dictatorship based mechanisms satisfies proportionality in expectation, which is a weaker definition of proportionality. Finally, we evaluate the efficiency obtained by our proposed mechanisms by computational experiments.

Original languageEnglish
Title of host publicationPRIMA 2015
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 18th International Conference, Proceedings
EditorsPaolo Torroni, Andrea Omicini, Jane Hsu, Qingliang Chen, Paolo Torroni, Andrea Omicini, Jane Hsu, Qingliang Chen, Serena Villata, Serena Villata
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319255231, 9783319255231
Publication statusPublished - Jan 1 2015
Event18th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2015 - Bertinoro, Italy
Duration: Oct 26 2015Oct 30 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other18th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2015

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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