Network creation games with local information and edge swaps

Shotaro Yoshimura, Yukiko Yamauchi

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


In the swap game (SG), selfish players, each of which is associated with a vertex, form a graph by edge swaps, i.e., a player changes its strategy by simultaneously removing an adjacent edge and forming a new edge (Alon et al. 2013). The cost of a player considers the average distance to all other players or the maximum distance to other players. Any SG by n players starting from a tree converges to an equilibrium with a constant Price of Anarchy (PoA) within O(n3) edge swaps (Lenzner 2011). We focus on SGs where each player knows the subgraph induced by players within distance k. Therefore, each player cannot compute its cost nor a best response. We first consider pessimistic players who consider the worst-case global graph. We show that any SG starting from a tree (i) always converges to an equilibrium within O(n3) edge swaps irrespective of the value of k, (ii) the PoA is Θ(n) for k=1,2,3, and (iii) the PoA is constant for k ≥4. We then introduce weakly pessimistic players and optimistic players and show that these less pessimistic players achieve constant PoA for k ≤3 at the cost of best response cycles.

Original languageEnglish
Title of host publicationStructural Information and Communication Complexity - 27th International Colloquium, SIROCCO 2020, Proceedings
EditorsAndrea Werneck Richa, Christian Scheideler
Number of pages17
ISBN (Print)9783030549206
Publication statusPublished - 2020
Event27th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2020 - Paderborn, Germany
Duration: Jun 29 2020Jul 1 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12156 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference27th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2020

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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