Information spread in networks: Control, games, and equilibria

Ali Khanafer, Tamer Basar

Research output: Contribution to conferencePaperpeer-review


We design intervention schemes to control information spread in multi-agent systems. We consider two information spread models: linear distributed averaging and virus spread dynamics. Using the framework of differential games, we design a dynamical optimization framework that produces strategies that are robust to adversarial intervention. For linear dynamics, we show that optimal strategies make connection to potential-theory. In the virus spread case, we show that optimal controllers exhibit multiple switches. Moreover, we establish a connection between game theory and dynamical descriptions of network epidemics, which provides insights into decision making in infected networks. Finally, we present initial building blocks for network controllability using a limited number of controls.

Original languageEnglish (US)
StatePublished - 2014
Event2014 IEEE Information Theory and Applications Workshop, ITA 2014 - San Diego, CA, United States
Duration: Feb 9 2014Feb 14 2014


Other2014 IEEE Information Theory and Applications Workshop, ITA 2014
Country/TerritoryUnited States
CitySan Diego, CA

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems


Dive into the research topics of 'Information spread in networks: Control, games, and equilibria'. Together they form a unique fingerprint.

Cite this