Verifying intervention policies to counter infection propagation over networks: A model checking approach

Ganesh Ram Santhanam, Yuly Suvorov, Samik Basu, Vasant Honavar

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

6 Scopus citations

Abstract

Spread of infections (diseases, ideas, etc.) in a network can be modeled as the evolution of states of nodes in a graph as a function of the states of their neighbors. Given an initial configuration of a network in which a subset of the nodes have been infected, and an infection propagation function that specifies how the states of the nodes evolve over time, we show how to use model checking to identify, verify, and evaluate the effectiveness of intervention policies for containing the propagation of infection over such networks.

Original languageEnglish (US)
Title of host publicationAAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference
Pages1408-1414
Number of pages7
StatePublished - 2011
Event25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11 - San Francisco, CA, United States
Duration: Aug 7 2011Aug 11 2011

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Other

Other25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
Country/TerritoryUnited States
CitySan Francisco, CA
Period8/7/118/11/11

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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