Network creation games with local information and edge swaps

Shotaro Yoshimura, Yukiko Yamauchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

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.

本文言語英語
ホスト出版物のタイトルStructural Information and Communication Complexity - 27th International Colloquium, SIROCCO 2020, Proceedings
編集者Andrea Werneck Richa, Christian Scheideler
出版社Springer
ページ349-365
ページ数17
ISBN(印刷版)9783030549206
DOI
出版ステータス出版済み - 2020
イベント27th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2020 - Paderborn, ドイツ
継続期間: 6 29 20207 1 2020

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12156 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議27th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2020
Countryドイツ
CityPaderborn
Period6/29/207/1/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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