Preventing HIV spread in homeless populations using PSINET

A. Yadav, L. Marcolino, E. Rice, R. Petering, H. Winetrobe, H. Rhoades, M. Tambe, H. Carmichael

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

8 Scopus citations


Homeless youth are prone to Human Immunodeficiency Virus (HIV) due to their engagement in high risk behavior such as unprotected sex, sex under influence of drugs, etc. Many non-profit agencies conduct interventions to educate and train a select group of homeless youth about HIV prevention and treatment practices and rely on word-of-mouth spread of information through their social network. Previous work in strategic selection of intervention participants does not handle un-certainties in the social network's structure and evolving network state, potentially causing significant shortcomings in spread of information. Thus, we developed PSINET, a decision support system to aid the agencies in this task. PSINET includes the following key novelties: (i) it handles uncertainties in network structure and evolving network state; (ii) it addresses these uncertainties by using POMDPs in influence maximization; and (iii) it provides algorithmic advances to allow high quality approximate solutions for such POMDPs. Simulations show that PSINET achieves more information spread over the current state-of-the-art. PSINET was developed in collaboration with My Friend's Place (a drop-in agency serving homeless youth in Los Angeles) and is currently being reviewed by their officials.

Original languageEnglish (US)
Title of host publicationPlanning, Search, and Optimization - Papers Presented at the 29th AAAI Conference on Artificial Intelligence, Technical Report
PublisherAI Access Foundation
Number of pages8
ISBN (Electronic)9781577357230
StatePublished - 2015
Event29th AAAI Conference on Artificial Intelligence, AAAI 2015 - Austin, United States
Duration: Jan 25 2015Jan 30 2015

Publication series

NameAAAI Workshop - Technical Report


Conference29th AAAI Conference on Artificial Intelligence, AAAI 2015
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • General Engineering


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