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

In three linesNeetyabhas presents a multi-agent simulation framework for optimizing public health policies under uncertainty. The model integrates 1,000 individual agents (masking, vaccination, shopping decisions) and policymakers using hierarchical RL agents (DQN, DDPG, TD3). Results show masking and vaccination significantly reduce epidemic peak height and duration.

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