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Full-Text Articles in Databases and Information Systems
Learning Index Policies For Restless Bandits With Application To Maternal Healthcare, Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Learning Index Policies For Restless Bandits With Application To Maternal Healthcare, Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe
Research Collection School Of Computing and Information Systems
In many community health settings, it is crucial to have a systematic monitoring and intervention process to ensure that the patients adhere to healthcare programs, such as periodic health checks or taking medications. When these interventions are expensive, they can be provided to only a fixed small fraction of the patients at any period of time. Hence, it is important to carefully choose the beneficiaries who should be provided with interventions and when. We model this scenario as a restless multi-armed bandit (RMAB) problem, where each beneficiary is assumed to transition from one state to another depending on the intervention …
Approximate Difference Rewards For Scalable Multigent Reinforcement Learning, Arambam James Singh, Akshat Kumar
Approximate Difference Rewards For Scalable Multigent Reinforcement Learning, Arambam James Singh, Akshat Kumar
Research Collection School Of Computing and Information Systems
We address the problem of multiagent credit assignment in a large scale multiagent system. Difference rewards (DRs) are an effective tool to tackle this problem, but their exact computation is known to be challenging even for small number of agents. We propose a scalable method to compute difference rewards based on aggregate information in a multiagent system with large number of agents by exploiting the symmetry present in several practical applications. Empirical evaluation on two multiagent domains—air-traffic control and cooperative navigation, shows better solution quality than previous approaches.