Agent Based Decision Support System Using Reinforcement Learning Under Emergency Circumstances

摘要

This paper deals with agent based decision support system for patient's right diagnosis and treatment under emergency circumstance. The well known reinforcement learning is utilized for modeling emergency healthcare system. Also designed is a novel interpretation of Markov decision process providing clear mathematical formulation to connect reinforcement learning as well as to express integrated agent system. Computational issues are also discussed with the corresponding solution procedure.