arXiv AI By Janani Venugopalan, Gaurav Deshkar, Rishabh Gaur, Harshal Hayatnagarkar, Jayanta Kshirsagar

Neetyabhas: A Framework for Uncertainty-Aware Public Policy Optimization in Rational Agent-Based Models

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arXiv:2606. 04562v1 Announce Type: new Abstract: Purpose The WHO's COVID-19 non-pharmaceutical interventions (e.

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arXiv AI
Aug 19

Adversarial Data Modeling in Epidemiology

The paper introduces a signaling‑game framework to model how individuals strategically misreport behavioral data—such as mask usage and vaccination status—to public health authorities. It provides a generative model of such adversarial data and a method for authorities to recover reliable signals, analyzing equilibrium outcomes and evaluating how deception affects epidemic control. Large‑scale simulations and real‑world validation show that well‑designed sender and receiver strategies can still maintain effective epidemic control even with pervasive dishonesty, and that behavioral distortions often follow structured patterns rather than random noise.

By Yiqi Su, Christo Kurisummoottil Thomas, Walid Saad, Sanmay Das, Bud Mishra, Naren Ramakrishnan
arXiv Machine Learning
Jul 21

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework

arXiv:2607. 16916v1 Announce Type: new Abstract: Bladder cancer treatment requires personalized and adaptive decision-making, particularly for recurrent disease, where treatment effectiveness changes across successive clinical episodes.

By Divyansh Chawla, Anshu Garg, Isshaan Singh