TY - JOUR
T1 - PSINET
T2 - Assisting HIV prevention among homeless youth by planning ahead
AU - Yadav, Amulya
AU - Marcolino, Leandro Soriano
AU - Rice, Eric
AU - Petering, Robin
AU - Winetrobe, Hailey
AU - Rhoades, Harmony
AU - Tambe, Milind
AU - Carmichael, Heather
N1 - Funding Information:
This research was supported by MURI Grant W911NF-11-1-0332. Rice, Rhoades, Winetrobe, and Petering were supported by NIMH Grant number R01-MH093336.
Publisher Copyright:
Copyright © 2016, Association for the Advancement of Artificial Intelligence. All rights reserved.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - Homeless youth are prone to human immun-odeficiency virus (HIV) due to their engagement in high-risk behavior such as unprotected sex, sex under influence of drugs, and so on. Many nonproft 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 one single social network Previous work in strategic selection of intervention participants does not handle uncertainties in the social networks' 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: (1) it handles uncertainties in network structure and evolving network state; (2) it addresses these uncertainties by using POMDPs in influence maximization; and (3) it provides algorithmic advances to allow high-quality approximate solutions for such POMDPs. Simulations show that PSINET achieves around 60 percent 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 its officials.
AB - Homeless youth are prone to human immun-odeficiency virus (HIV) due to their engagement in high-risk behavior such as unprotected sex, sex under influence of drugs, and so on. Many nonproft 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 one single social network Previous work in strategic selection of intervention participants does not handle uncertainties in the social networks' 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: (1) it handles uncertainties in network structure and evolving network state; (2) it addresses these uncertainties by using POMDPs in influence maximization; and (3) it provides algorithmic advances to allow high-quality approximate solutions for such POMDPs. Simulations show that PSINET achieves around 60 percent 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 its officials.
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U2 - 10.1609/aimag.v37i2.2632
DO - 10.1609/aimag.v37i2.2632
M3 - Article
AN - SCOPUS:85019974071
SN - 0738-4602
VL - 37
SP - 47
EP - 62
JO - AI Magazine
JF - AI Magazine
IS - 2
ER -