b'Milind Tambe'

research

∙ 08/17/2023

Equitable Restless Multi-Armed Bandits: A General Framework Inspired By Digital Health

Restless multi-armed bandits (RMABs) are a popular framework for algorit...

0 Jackson A. Killian, et al. ∙

research

∙ 07/17/2023

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

In this white paper, we synthesize key points made during presentations ...

0 Lily Xu, et al. ∙

research

∙ 05/22/2023

Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcare

The success of many healthcare programs depends on participants' adheren...

6 Panayiotis Danassis, et al. ∙

research

∙ 03/01/2023

Fairness for Workers Who Pull the Arms: An Index Based Policy for Allocation of Restless Bandit Tasks

Motivated by applications such as machine repair, project monitoring, an...

0 Arpita Biswas, et al. ∙

research

∙ 02/06/2023

Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation

We consider the task of evaluating policies of algorithmic resource allo...

2 Aditya Mate, et al. ∙

research

∙ 01/19/2023

Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits

Restless multi-arm bandits (RMABs) is a popular decision-theoretic frame...

3 Paritosh Verma, et al. ∙

research

∙ 10/31/2022

Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits

We study the problem of planning restless multi-armed bandits (RMABs) wi...

9 Abheek Ghosh, et al. ∙

research

∙ 10/31/2022

Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence

In September 2016, Stanford's "One Hundred Year Study on Artificial Inte...

0 Peter Stone, et al. ∙

research

∙ 09/30/2022

Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits

While standard bandit algorithms sometimes incur high regret, their perf...

18 Siddhartha Banerjee, et al. ∙

research

∙ 05/30/2022

Optimistic Whittle Index Policy: Online Learning for Restless Bandits

Restless multi-armed bandits (RMABs) extend multi-armed bandits to allow...

13 Kai Wang, et al. ∙

research

∙ 05/11/2022

Ranked Prioritization of Groups in Combinatorial Bandit Allocation

Preventing poaching through ranger patrols protects endangered wildlife,...

0 Lily Xu, et al. ∙

research

∙ 04/29/2022

Evolutionary Approach to Security Games with Signaling

Green Security Games have become a popular way to model scenarios involv...

14 Adam Żychowski, et al. ∙

research

∙ 04/28/2022

ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria

More than 5 million children under five years die from largely preventab...

18 Vineet Nair, et al. ∙

research

∙ 02/28/2022

Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022

The workshop will focus on the application of AI to problems in cyber se...

0 James Holt, et al. ∙

research

∙ 01/28/2022

Networked Restless Multi-Armed Bandits for Mobile Interventions

Motivated by a broad class of mobile intervention problems, we propose a...

12 Han-Ching Ou, et al. ∙

research

∙ 09/22/2021

Facilitating human-wildlife cohabitation through conflict prediction

With increasing world population and expanded use of forests as cohabite...

9 Susobhan Ghosh, et al. ∙

research

∙ 09/16/2021

Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health

The widespread availability of cell phones has enabled non-profits to de...

13 Aditya Mate, et al. ∙

research

∙ 07/07/2021

Harnessing Heterogeneity: Learning from Decomposed Feedback in Bayesian Modeling

There is significant interest in learning and optimizing a complex syste...

4 Kai Wang, et al. ∙

research

∙ 07/04/2021

Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning

We introduce Robust Restless Bandits, a challenging generalization of re...

20 Jackson A. Killian, et al. ∙

research

∙ 06/13/2021

Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

The influence maximization (IM) problem aims at finding a subset of seed...

23 Haipeng Chen, et al. ∙

research

∙ 06/08/2021

Solving Structured Hierarchical Games Using Differential Backward Induction

Many real-world systems possess a hierarchical structure where a strateg...

0 Zun Li, et al. ∙

research

∙ 06/06/2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning

In the predict-then-optimize framework, the objective is to train a pred...

29 Kai Wang, et al. ∙

research

∙ 06/06/2021

Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games

A growing body of work in game theory extends the traditional Stackelber...

0 Kai Wang, et al. ∙

research

∙ 05/17/2021

Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

In many public health settings, it is important for patients to adhere t...

23 Arpita Biswas, et al. ∙

research

∙ 03/08/2021

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

Restless Multi-Armed Bandits (RMABs) have been popularly used to model l...

20 Aditya Mate, et al. ∙

research

∙ 02/21/2021

A Game-Theoretic Approach for Hierarchical Policy-Making

We present the design and analysis of a multi-level game-theoretic model...

0 Feiran Jia, et al. ∙

research

∙ 01/07/2021

Active Screening for Recurrent Diseases: A Reinforcement Learning Approach

Active screening is a common approach in controlling the spread of recur...

9 Han-Ching Ou, et al. ∙

research

∙ 12/23/2020

Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway

The Mumbai Suburban Railways, locals, are a key transit infrastructure o...

0 Alok Talekar, et al. ∙

research

∙ 12/18/2020

Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty

Green Security Games (GSGs) have been successfully used in the protectio...

0 Aravind Venugopal, et al. ∙

research

∙ 12/07/2020

Efficient Reservoir Management through Deep Reinforcement Learning

Dams impact downstream river dynamics through flow regulation and disrup...

18 Xinrun Wang, et al. ∙

research

∙ 11/20/2020

Enhancing Poaching Predictions for Under-Resourced Wildlife Conservation Parks Using Remote Sensing Imagery

Illegal wildlife poaching is driving the loss of biodiversity. To combat...

22 Rachel Guo, et al. ∙

research

∙ 11/05/2020

Measuring Data Collection Quality for Community Healthcare

Machine learning has tremendous potential to provide targeted interventi...

29 Ramesha Karunasena, et al. ∙

research

∙ 09/14/2020

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security

Conservation efforts in green security domains to protect wildlife and f...

5 Lily Xu, et al. ∙

research

∙ 09/12/2020

Tracking disease outbreaks from sparse data with Bayesian inference

The COVID-19 pandemic provides new motivation for a classic problem in e...

8 Bryan Wilder, et al. ∙

research

∙ 07/11/2020

Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness

Each year, there are nearly 4 million youth experiencing homelessness (Y...

0 Eric Rice, et al. ∙

research

∙ 07/05/2020

Collapsing Bandits and Their Application to Public Health Interventions

We propose and study Collpasing Bandits, a new restless multi-armed band...

11 Aditya Mate, et al. ∙

research

∙ 06/22/2020

Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers

Applications of artificial intelligence for wildlife protection have foc...

0 Lily Xu, et al. ∙

research

∙ 06/18/2020

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

Solving optimization problems with unknown parameters often requires lea...

0 Kai Wang, et al. ∙

research

∙ 06/14/2020

Fair Influence Maximization: A Welfare Optimization Approach

Several social interventions (e.g., suicide and HIV prevention) leverage...

10 Aida Rahmattalabi, et al. ∙

research

∙ 06/13/2020

Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement

India accounts for 11% of maternal deaths globally where a woman dies in...

0 Siddharth Nishtala, et al. ∙

research

∙ 12/16/2019

AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline

With the maturing of AI and multiagent systems research, we have a treme...

0 Andrew Perrault, et al. ∙

research

∙ 11/20/2019

Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning

Large-scale screening for potential threats with limited resources and c...

7 Sanket Shah, et al. ∙

research

∙ 07/12/2019

MIPaaL: Mixed Integer Program as a Layer

Machine learning components commonly appear in larger decision-making pi...

2 Aaron Ferber, et al. ∙

research

∙ 05/31/2019

End to end learning and optimization on graphs

Real-world applications often combine learning and optimization problems...

10 Bryan Wilder, et al. ∙

research

∙ 03/08/2019

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Illegal wildlife poaching threatens ecosystems and drives endangered spe...

0 Shahrzad Gholami, et al. ∙

research

∙ 03/03/2019

Group-Fairness in Influence Maximization

Influence maximization is a widely used model for information disseminat...

0 Alan Tsang, et al. ∙

research

∙ 03/03/2019

Decision-Focused Learning of Adversary Behavior in Security Games

Stackelberg security games are a critical tool for maximizing the utilit...

0 Andrew Perrault, et al. ∙

research

∙ 02/05/2019

Learning to Prescribe Interventions for Tuberculosis Patients using Digital Adherence Data

Digital Adherence Technologies (DATs) are an increasingly popular method...

14 Jackson A. Killian, et al. ∙

research

∙ 01/16/2019

Artificial Intelligence for Social Good

The Computing Community Consortium (CCC), along with the White House Off...

0 Gregory D. Hager, et al. ∙

research

∙ 11/09/2018

On the Inducibility of Stackelberg Equilibrium for Security Games

Strong Stackelberg equilibrium (SSE) is the standard solution concept of...

0 Qingyu Guo, et al. ∙

Milind Tambe

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