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Hauptverfasser:	Syed, Toqeer Ali, Akarma, Ali, Ali, Ahmad, Lee, It Ee, Jan, Salman, Khan, Sohail, Nauman, Muhammad
Format:	Recurso digital
Sprache:
Veröffentlicht:	Zenodo 2026
Schlagworte:	agentic AI IoT healthcare reinforcement learning BDI agents privacy-preserving human-in-the-loop chronic disease management MIMIC-IV constrained MDP
Online-Zugang:	https://doi.org/10.5281/zenodo.18891708
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Inhaltsangabe:

Official implementation of the PAAI framework — a four-layer constrained reinforcement learning and BDI multi-agent architecture for chronic disease management in IoT healthcare. Combines a custom Gymnasium environment, MaskablePPO with Lagrangian safety constraints, a hash-chained audit log, and a three-tier Human-in-the-Loop governance model. Validated on a 12-month synthetic cohort of 500 patients and on MIMIC-IV real ICU data.