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Massachusetts Institute of Technology

Smoothed Complexity of Network Coordination Games

Abstract

dc:description.abstract

The problem of finding or computing Nash equilibria has been an important problem in economics and computer science for decades. Classical worst-case and expectedcase analyses have shown that in many cases for many types of games, computing Nash equilibria is intractable. However, it has been empirically shown that in many instances, approximate Nash equilibria can be computed efficiently. Thus, there is a growing interest in the smoothed complexity of games. That is, the complexity of computing Nash equilibria when the inputs to the problem are confined to look more like real-world inputs. This thesis provides a further analysis of the smoothed complexity of network coordination games. We specifically look at the smoothed complexity of the 2-Flip algorithm. While we do not prove that using the 2-Flip algorithm on 2-Flip-Max-Cut achieves smoothed quasipolynomial time, we discuss multiple attempts at this goal, and hope to provide other researchers with the inspiration to prove quasipolynomial time.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Viera, Julian T.
Advisor dc:contributor.advisor
  • Daskalakis, Constantinos

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/145081
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/145081

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Viera, Julian T.. Smoothed Complexity of Network Coordination Games. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/145081