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We propose an incentive scheme based on intervention to sustain cooperation among self-interested users. In the proposed scheme, an intervention device collects imperfect signals about the actions of the users for a test period, and then…

Computer Science and Game Theory · Computer Science 2010-12-09 Jaeok Park , Mihaela van der Schaar

We address the personalized policy learning problem using longitudinal mobile health application usage data. Personalized policy represents a paradigm shift from developing a single policy that may prescribe personalized decisions by…

Methodology · Statistics 2020-01-13 Xinyu Hu , Min Qian , Bin Cheng , Ying Kuen Cheung

Educational games enhance learning experiences by integrating touchscreens, making interactions more engaging and intuitive for learners. However, the cognitive impacts of educational gameplay input modalities, such as the hand and stylus…

Human-Computer Interaction · Computer Science 2025-10-29 Shayla Sharmin , Elham Bakhshipour , Behdokht Kiafar , Md Fahim Abrar , Pinar Kullu , Nancy Getchell , Roghayeh Leila Barmaki

We study a sequential resource allocation problem where a decision maker selects subsets of agents at each period to maximize overall outcomes without prior knowledge of individual-level effects. Our framework applies to settings such as…

Machine Learning · Computer Science 2025-08-29 Katherine B. Adams , Justin J. Boutilier , Qinyang He , Yonatan Mintz

The frequency with which people interact with technology means that users may develop interface habits, i.e. fast, automatic responses to stable interface cues. Design guidelines often assume that interface habits are beneficial. However,…

Human-Computer Interaction · Computer Science 2020-05-15 Diego Garaialde , Christopher P. Bowers , Charlie Pinder , Priyal Shah , Shashwat Parashar , Leigh Clark , Benjamin R. Cowan

Sequential experiments are often characterized by an exploration-exploitation tradeoff that is captured by the multi-armed bandit (MAB) framework. This framework has been studied and applied, typically when at each time period feedback is…

Machine Learning · Computer Science 2020-12-22 Yonatan Gur , Ahmadreza Momeni

Language agents have demonstrated remarkable potential in web search and information retrieval. However, these search agents assume user queries are complete and unambiguous, an assumption that diverges from reality where users begin with…

In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the "gold-standard" methodology for developing such interventions. Analyzing data from these trials…

Methodology · Statistics 2024-07-31 Xueqing Liu , Tianchen Qian , Lauren Bell , Bibhas Chakraborty

Interactive Fiction (IF) games with real human-written natural language texts provide a new natural evaluation for language understanding techniques. In contrast to previous text games with mostly synthetic texts, IF games pose language…

Computation and Language · Computer Science 2020-10-07 Xiaoxiao Guo , Mo Yu , Yupeng Gao , Chuang Gan , Murray Campbell , Shiyu Chang

The ubiquity and on-the-go availability of mobile devices makes them central to many tasks such as interpersonal communication and media consumption. However, despite the potential of mobile devices for on-demand exploratory data…

Human-Computer Interaction · Computer Science 2024-04-18 Luke S. Snyder , Ryan A. Rossi , Eunyee Koh , Jeffrey Heer , Jane Hoffswell

Prior research has shown that students' problem-solving pathways in game-based learning environments reflect their conceptual understanding, procedural knowledge, and flexibility. Replay behaviors, in particular, may indicate productive…

Computers and Society · Computer Science 2026-01-21 Shan Zhang , Siddhartha Pradhan , Ji-Eun Lee , Ashish Gurung , Anthony F. Botelho

Pragmatic trials increasingly define outcomes using real-world data such as electronic health records, where assessments are collected during routine care rather than at fixed timepoints. Consequently, these uncontrolled assessments may be…

Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking personalized needs, leading to significant limitations for real…

Computation and Language · Computer Science 2026-01-29 Shuoxin Wang , Chang Liu , Gowen Loo , Lifan Zheng , Kaiwen Wei , Xinyi Zeng , Jingyuan Zhang , Yu Tian

Construction of just-in-time adaptive interventions, such as prompts delivered by mobile apps to promote and maintain behavioral change, requires knowledge about time-varying moderated effects to inform when and how we deliver intervention…

Methodology · Statistics 2022-12-06 Jieru Shi , Zhenke Wu , Walter Dempsey

This paper studies multi-user communication systems with two groups of users: leaders which possess system information, and followers which have no system information using the formulation of Stackelberg games. In such games, the leaders…

Information Theory · Computer Science 2011-08-26 saeedeh parsaeefard , Mihaela van der Schaar , Ahmad R. Sharafat

Games are challenging for Reinforcement Learning~(RL) agents due to their reward-sparsity, as rewards are only obtainable after long sequences of deliberate actions. Intrinsic Motivation~(IM) methods -- which introduce exploration rewards…

Artificial Intelligence · Computer Science 2025-07-29 Leonardo Villalobos-Arias , Grant Forbes , Jianxun Wang , David L Roberts , Arnav Jhala

User engagement is crucial to the long-term success of a mobile app. Several metrics, such as dwell time, have been used for measuring user engagement. However, how to effectively predict user engagement in the context of mobile apps is…

Information Retrieval · Computer Science 2021-06-04 Yuan Tian , Ke Zhou , Dan Pelleg

Mobile health (mHealth) technologies empower patients to adopt/maintain healthy behaviors in their daily lives, by providing interventions (e.g. push notifications) tailored to the user's needs. In these settings, without intervention,…

Machine Learning · Computer Science 2022-12-05 Eura Shin , Siddharth Swaroop , Weiwei Pan , Susan Murphy , Finale Doshi-Velez

Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real world evidence to assess device safety and track…

Computers and Society · Computer Science 2019-04-17 Alison Callahan , Jason A Fries , Christopher Ré , James I Huddleston , Nicholas J Giori , Scott Delp , Nigam H Shah

This study investigates behavioral intention to use healthcare metaverse platforms among medical students and physicians in Turkey, where such technologies are in early stages of adoption. A multi-theoretical research model was developed by…

Human-Computer Interaction · Computer Science 2025-10-21 Seckin Damar , Gulsah Hancerliogullari Koksalmis