Date of Award


Publication Type

Master Thesis

Degree Name



Computer Science

First Advisor

Kobti, Ziad (School of Computer Science)


Computer Science.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


Health practitioners are studying different techniques to provide quality patient care and to prevent injuries in the hospitals, which motivate the ground work to model such a complex system with the objective to understand the chief social factors leading to injury. The underlying social factors such as socialization, task scheduling, domain knowledge and path finding contribute to the day-to-day activity of the health practitioners and agents in social models which ultimately affect their performance. The aim of this study is to outline the objective decision support elements in mission critical human social models and critically examine the influence of those factors on the system. The outcome of this research leads to a development of more realistic artificial agents in a social complex modeling for the better understanding of the system's behavior.