The role of a-priori information in networks of rational agents

Yehuda Afek, Shaked Rafaeli, Moshe Sulamy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Until now, distributed algorithms for rational agents have assumed a-priori knowledge of n, the size of the network. This assumption is challenged here by proving how much a-priori knowledge is necessary for equilibrium in different distributed computing problems. Duplication – pretending to be more than one agent – is the main tool used by agents to deviate and increase their utility when not enough knowledge about n is given. We begin by proving that when no information on n is given, equilibrium is impossible for both Coloring and Knowledge Sharing. We then provide new algorithms for both problems when n is a-priori known to all agents. However, what if agents have partial knowledge about n? We provide tight upper and lower bounds that must be a-priori known on n for equilibrium to be possible in Leader Election, Knowledge Sharing, Coloring, Partition and Orientation.

Original languageEnglish
Title of host publication32nd International Symposium on Distributed Computing, DISC 2018
EditorsUlrich Schmid, Josef Widder
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959770927
DOIs
StatePublished - 1 Oct 2018
Event32nd International Symposium on Distributed Computing, DISC 2018 - New Orleans, United States
Duration: 15 Oct 201819 Oct 2018

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume121
ISSN (Print)1868-8969

Conference

Conference32nd International Symposium on Distributed Computing, DISC 2018
Country/TerritoryUnited States
CityNew Orleans
Period15/10/1819/10/18

Keywords

  • And phrases rational agents
  • Coloring
  • Distributed game theory
  • Knowledge sharing

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