AINeutralarXiv – CS AI · 8h ago5/10
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Neetyabhas: A Framework for Uncertainty-Aware Public Policy Optimization in Rational Agent-Based Models
Researchers developed Neetyabhas, an agent-based simulation framework that models pandemic policy decisions under real-world uncertainty, incorporating individual behavioral choices and imperfect data. Using reinforcement learning, the model demonstrates that masks and vaccines effectively reduce outbreak severity when policies account for implementation errors and measurement gaps.