no code implementations • 23 Nov 2023 • Bill Tang, Çağıl Koçyiğit, Eric Rice, Phebe Vayanos
We study the problem of allocating scarce societal resources of different types (e. g., permanent housing, deceased donor kidneys for transplantation, ventilators) to heterogeneous allocatees on a waitlist (e. g., people experiencing homelessness, individuals suffering from end-stage renal disease, Covid-19 patients) based on their observed covariates.
no code implementations • 4 Dec 2022 • Nathanael Jo, Bill Tang, Kathryn Dullerud, Sina Aghaei, Eric Rice, Phebe Vayanos
We study critical systems that allocate scarce resources to satisfy basic needs, such as homeless services that provide housing.
no code implementations • 25 Jan 2022 • Aida Rahmattalabi, Phebe Vayanos, Kathryn Dullerud, Eric Rice
The resources are assigned in a first come first served (FCFS) fashion according to an eligibility structure that encodes the resource types that serve each queue.
no code implementations • 14 Jun 2020 • Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe
Under this framework, the trade-off between fairness and efficiency can be controlled by a single inequality aversion design parameter.
no code implementations • 4 Mar 2020 • Phebe Vayanos, Yingxiao Ye, Duncan McElfresh, John Dickerson, Eric Rice
For the offline case, where active preference elicitation takes the form of a two and half stage robust optimization problem with decision-dependent information discovery, we provide an equivalent reformulation in the form of a mixed-binary linear program which we solve via column-and-constraint generation.
1 code implementation • 3 Mar 2019 • Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick
Influence maximization is a widely used model for information dissemination in social networks.
Computer Science and Game Theory Social and Information Networks
no code implementations • 19 Aug 2016 • Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Amulya Yadav, Milind Tambe
To pilot test an artificial intelligence (AI) algorithm that selects peer change agents (PCA) to disseminate HIV testing messaging in a population of homeless youth.
no code implementations • 30 Jan 2016 • Amulya Yadav, Hau Chan, Albert Jiang, Haifeng Xu, Eric Rice, Milind Tambe
This paper presents HEALER, a software agent that recommends sequential intervention plans for use by homeless shelters, who organize these interventions to raise awareness about HIV among homeless youth.