Abstract
In sequential decision making, we program agent by reward and punishment. In this, agent learns to map situations to actions which results in maximizing rewards gained. This agent is also known as decision makers. It is difficult to take decision about giving specific kind and quantity of insulin dose to the diabetes patient in a critical system of insulin pump control. This paper implements the Q learning algorithm on diabetes data streams. This helps in classifying the data for diabetes dose and also helps in making decision about giving particular kind and quantity of insulin dose by generating various rules.
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Patil, P., Kulkarni, P., Shirsath, R. (2015). Sequential Decision Making Using Q Learning Algorithm for Diabetic Patients. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 324. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2126-5_35
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DOI: https://doi.org/10.1007/978-81-322-2126-5_35
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