An Autonomous Multi-Agent Simulation Model for Acute Inflammatory Response

2011 ◽  
Vol 2 (2) ◽  
pp. 105-121 ◽  
Author(s):  
John Wu ◽  
David Ben-Arieh ◽  
Zhenzhen Shi

This research proposes an agent-based simulation model combined with the strength of systemic dynamic mathematical model, providing a new modeling and simulation approach of the pathogenesis of AIR. AIR is the initial stage of a typical sepsis episode, often leading to severe sepsis or septic shocks. The process of AIR has been in the focal point affecting more than 750,000 patients annually in the United State alone. Based on the agent-based model presented herein, clinicians can predict the sepsis pathogenesis for patients using the prognostic indicators from the simulation results, planning the proper therapeutic interventions accordingly. Impressively, the modeling approach presented creates a friendly user-interface allowing physicians to visualize and capture the potential AIR progression patterns. Based on the computational studies, the simulated behavior of the agent–based model conforms to the mechanisms described by the system dynamics mathematical models established in previous research.

Author(s):  
John Wu ◽  
David Ben-Arieh ◽  
Zhenzhen Shi

This research proposes an agent-based simulation model combined with the strength of systemic dynamic mathematical model, providing a new modeling and simulation approach of the pathogenesis of AIR. AIR is the initial stage of a typical sepsis episode, often leading to severe sepsis or septic shocks. The process of AIR has been in the focal point affecting more than 750,000 patients annually in the United State alone. Based on the agent-based model presented herein, clinicians can predict the sepsis pathogenesis for patients using the prognostic indicators from the simulation results, planning the proper therapeutic interventions accordingly. Impressively, the modeling approach presented creates a friendly user-interface allowing physicians to visualize and capture the potential AIR progression patterns. Based on the computational studies, the simulated behavior of the agent–based model conforms to the mechanisms described by the system dynamics mathematical models established in previous research.


2014 ◽  
Vol 1030-1032 ◽  
pp. 2044-2049
Author(s):  
Can Can Zhao ◽  
Xiao Hong Guo ◽  
Juxihong Julaiti ◽  
Jie Wang

In order to analyze the evacuation behaviors and optimize evacuation strategies for rail transit system, an evacuation agent centered simulation model was proposed. Firstly, by considering the attributes, status and decision-making behaviors of evacuation personnel, the evacuation agent model was established, and the running principle as well as construction process of multi-agent simulation model was discussed. Then, the specific definition and design for the agent attributes and evacuation behavior protocol were provided. Finally, based on the simulation model proposed, an evacuation simulation platform for the military museum station of Beijing subway line 9 was established by using REPAST and JAVA, several evacuation strategies were tested and optimized.


Author(s):  
Ulf Lotzmann

In this chapter an agent-based traffic simulation approach is presented which sees agents as individual traffic participants moving in an artificial environment. There is no restriction on types of players, such as car drivers or pedestrians. A concept is introduced which is appropriate to model different kinds of traffic participants and to have them interact with each other in one single scenario. The scenario may not only include roads, but also stadiums, shopping malls and any other situations where pedestrians or vehicles of any kind move around. Core theme of the chapter is an agent model that is founded on a layered architecture. Experiences with implementation and usage of the agent model within the universal multi-agent simulation framework TRASS will be explained by means of several application examples which also support discussion about validation of concept and implementation.


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