Several relaxations of envy-freeness, tailored to fair division in settings with indivisible goods, have been introduced within the last decade. Due to the lack of general existence results for most of these concepts, great attention has been paid to establishing approximation guarantees. In this work, we propose a simple algorithm that is universally fair in the sense that it returns allocations that have good approximation guarantees with respect to four such fairness notions at once. In particular, this is the first algorithm achieving a (φ−1)-approximation of envy-freeness up to any good (EFX) and a 2/φ+2 -approximation of groupwise maximin share fairness (GMMS), where φ is the golden ratio. The best known approximation factor, in polynomial time, for either one of these fairness notions prior to this work was 1/2. Moreover, the returned allocation achieves envy-freeness up to one good (EF1) and a 2/3-approximation of pairwise maximin share fairness (PMMS). While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve further the guarantees for GMMS or PMMS. Finally, we show that GMMS—and thus PMMS and EFX—allocations always exist when the number of goods does not exceed the number of agents by more than two.

Multiple Birds with One Stone: Beating 1/2 for EFX and GMMS via Envy Cycle Elimination / Amanatidis, Georgios; Markakis, Evangelos; Ntokos, Apostolos. - 34:02(2020), pp. 1790-1797. (Intervento presentato al convegno The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) tenutosi a New York, New York, USA.) [10.1609/aaai.v34i02.5545].

Multiple Birds with One Stone: Beating 1/2 for EFX and GMMS via Envy Cycle Elimination

Amanatidis, Georgios;
2020

Abstract

Several relaxations of envy-freeness, tailored to fair division in settings with indivisible goods, have been introduced within the last decade. Due to the lack of general existence results for most of these concepts, great attention has been paid to establishing approximation guarantees. In this work, we propose a simple algorithm that is universally fair in the sense that it returns allocations that have good approximation guarantees with respect to four such fairness notions at once. In particular, this is the first algorithm achieving a (φ−1)-approximation of envy-freeness up to any good (EFX) and a 2/φ+2 -approximation of groupwise maximin share fairness (GMMS), where φ is the golden ratio. The best known approximation factor, in polynomial time, for either one of these fairness notions prior to this work was 1/2. Moreover, the returned allocation achieves envy-freeness up to one good (EF1) and a 2/3-approximation of pairwise maximin share fairness (PMMS). While EFX is our primary focus, we also exhibit how to fine-tune our algorithm and improve further the guarantees for GMMS or PMMS. Finally, we show that GMMS—and thus PMMS and EFX—allocations always exist when the number of goods does not exceed the number of agents by more than two.
2020
The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20)
envy-free; groupwise maximin share fairness; EFX
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Multiple Birds with One Stone: Beating 1/2 for EFX and GMMS via Envy Cycle Elimination / Amanatidis, Georgios; Markakis, Evangelos; Ntokos, Apostolos. - 34:02(2020), pp. 1790-1797. (Intervento presentato al convegno The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) tenutosi a New York, New York, USA.) [10.1609/aaai.v34i02.5545].
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1504595
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact