Development of a Hybrid Machine Learning Agent Based Model for Optimization and Interpretability

Author(s):  
Paul Cummings ◽  
Andrew Crooks
Author(s):  
Marek Laskowski

Science is on the verge of practical agent based modeling decision support systems capable of machine learning for healthcare policy decision support. The details of integrating an agent based model of a hospital emergency department with a genetic programming machine learning system are presented in this paper. A novel GP heuristic or extension is introduced to better represent the Markov Decision Process that underlies agent decision making in an unknown environment. The capabilities of the resulting prototype for automated hypothesis generation within the context of healthcare policy decision support are demonstrated by automatically generating patient flow and infection spread prevention policies. Finally, some observations are made regarding moving forward from the prototype stage.


2020 ◽  
Vol 72 ◽  
pp. 101590 ◽  
Author(s):  
Stathis Polyzos ◽  
Aristeidis Samitas ◽  
Marina-Selini Katsaiti

2018 ◽  
Vol 90 ◽  
pp. 366-389 ◽  
Author(s):  
Francesco Lamperti ◽  
Andrea Roventini ◽  
Amir Sani

Sign in / Sign up

Export Citation Format

Share Document