Search Results for author: Aditya Mate

Found 7 papers, 1 papers with code

Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Care Domain

no code implementations2 Feb 2022 Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe

To address this shortcoming we propose a novel approach for decision-focused learning in RMAB that directly trains the predictive model to maximize the Whittle index solution quality.

Multi-Armed Bandits

Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems

no code implementations8 Mar 2021 Aditya Mate, Arpita Biswas, Christoph Siebenbrunner, Susobhan Ghosh, Milind Tambe

Our contributions are as follows: (1) We derive conditions under which our problem satisfies indexability, a precondition that guarantees the existence and asymptotic optimality of the Whittle Index solution for RMABs.

Multi-Armed Bandits

Collapsing Bandits and Their Application to Public Health Intervention

1 code implementation NeurIPS 2020 Aditya Mate, Jackson Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

Our main contributions are as follows: (i) Building on the Whittle index technique for RMABs, we derive conditions under which the Collapsing Bandits problem is indexable.

Collapsing Bandits and Their Application to Public Health Interventions

no code implementations5 Jul 2020 Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

(ii) We exploit the optimality of threshold policies to build fast algorithms for computing the Whittle index, including a closed-form.

End-to-End Game-Focused Learning of Adversary Behavior in Security Games

no code implementations3 Mar 2019 Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe

Stackelberg security games are a critical tool for maximizing the utility of limited defense resources to protect important targets from an intelligent adversary.

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