(3) We show the applicability of these results for catering to three real-world CHW considerations including: (i) risk-sensitive planning, (ii) fairness.

May 3, 2021 · Previous work has developed several classes of Restless Multi-Armed Bandits (RMABs) that are computationally tractable and indexable, a ...

Jul 23, 2021 · Abstract: Community Health Workers (CHWs) form an important component of health-care systems globally, especially in low-resource settings.

Mar 15, 2024 · We propose a restless multiarmed bandit (RMAB) model to plan interventions that jointly optimize long-term engagement and individual clinical outcomes.

Risk-aware interventions in public health: Planning with restless multi-armed bandits. In Proceed- ings of the 20th International Conference on Autonomous.

Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. (2021). [10] Luke Merrick and Ankur Taly. 2019. The Explanation Game: ...

We define a new subclass of the restless multi-armed ban- dit framework, that we name Adherence Bandits, designed to capture the dynamics prevalent in many ...

Restless Multi-Armed Bandits (RMAB) is an apt model to represent decision-making problems in public health interventions (e.g., tuberculosis, ma-.

ABSTRACT. Motivated by a broad class of mobile intervention problems, we pro- pose and study restless multi-armed bandits (RMABs) with network effects.

We propose and study Collapsing Bandits, a new restless multi-armed bandit. (RMAB) setting in which each arm follows a binary-state Markovian process.