Welfare Maximization with Limited Interaction

Noga Alon, Noam Nisan, Ran Raz, Omri Weinstein

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

22 Scopus citations


We continue the study of welfare maximization in unit-demand (matching) markets, in a distributed information model where agent's valuations are unknown to the central planner, and therefore communication is required to determine an efficient allocation. Dobzinski, Nisan and Oren (STOC'14) showed that if the market size is n, then r rounds of interaction (with logarithmic bandwidth) suffice to obtain an n(1/(r+1))-approximation to the optimal social welfare. In particular, this implies that such markets converge to a stable state (constant approximation) in time logarithmic in the market size. We obtain the first multi-round lower bound for this setup. We show that even if the allowable per-round bandwidth of each agent is nε(r), the approximation ratio of any r-round (randomized) protocol is no better than Omega(n(exp(-r)), implying an Omega(log log n) lower bound on the rate of convergence of the market to equilibrium. Our construction and technique may be of interest to round-communication tradeoffs in the more general setting of combinatorial auctions, for which the only known lower bound is for simultaneous (r = 1) protocols [DNO14].

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, FOCS 2015
PublisherIEEE Computer Society
Number of pages14
ISBN (Electronic)9781467381918
StatePublished - Dec 11 2015
Externally publishedYes
Event56th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2015 - Berkeley, United States
Duration: Oct 17 2015Oct 20 2015

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
ISSN (Print)0272-5428


Other56th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2015
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • General Computer Science


  • Distributed matchings
  • Information theory
  • Multiparty Communication complexity
  • Welfare maximization


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