scholarly journals A SIMULATION-AS-A-SERVICE FRAMEWORK FACILITATING WEBGIS BASED INSTALLATION PLANNING

Author(s):  
Z. Zheng ◽  
Z. Y. Chang ◽  
Y. F. Fei

Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users’ operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents’ process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

Author(s):  
H. Faroqi ◽  
M.-S. Mesgari

During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.


Author(s):  
Takeshi Takenaka ◽  
Kousuke Fujita ◽  
Nariaki Nishino ◽  
Tsukasa Ishigaki ◽  
Yoichi Motomura

Science and technology are expected to support actual service provision and to create new services to promote service industries’ productivity. However, those problems might not be solved solely in a certain research area. This paper describes that it is necessary to establish transdisciplinary approaches to service design in consideration of consumers’ values and decision making. Recent research trends of services are overviewed. Then a research framework is proposed to integrate computer sciences, human sciences, and economic sciences. Three study examples of services are then presented. The first study is a multi-agent simulation of a cellular telephone market based on results of a psychological survey. The second presents a cognitive model constructed through integration of questionnaire data of a retail business and Bayesian network modeling. The third presents a pricing mechanism design for service facilities––movie theaters––using an economic experiment and agent-based simulation.


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):  
Takeshi Takenaka ◽  
Kousuke Fujita ◽  
Nariaki Nishino ◽  
Tsukasa Ishigaki ◽  
Yoichi Motomura

Science and technology are expected to support actual service provision and to create new services to promote service industries’ productivity. However, those problems might not be solved solely in a certain research area. This paper describes that it is necessary to establish transdisciplinary approaches to service design in consideration of consumers’ values and decision making. Recent research trends of services are overviewed. Then a research framework is proposed to integrate computer sciences, human sciences, and economic sciences. Three study examples of services are then presented. The first study is a multi-agent simulation of a cellular telephone market based on results of a psychological survey. The second presents a cognitive model constructed through integration of questionnaire data of a retail business and Bayesian network modeling. The third presents a pricing mechanism design for service facilities––movie theaters––using an economic experiment and agent-based simulation.


SIMULATION ◽  
2016 ◽  
Vol 93 (1) ◽  
pp. 69-84 ◽  
Author(s):  
Shailesh Tamrakar ◽  
Paul Richmond ◽  
Roshan M D’Souza

Agent-based models (ABMs) are increasingly being used to study population dynamics in complex systems, such as the human immune system. Previously, Folcik et al. (The basic immune simulator: an agent-based model to study the interactions between innate and adaptive immunity. Theor Biol Med Model 2007; 4: 39) developed a Basic Immune Simulator (BIS) and implemented it using the Recursive Porous Agent Simulation Toolkit (RePast) ABM simulation framework. However, frameworks such as RePast are designed to execute serially on central processing units and therefore cannot efficiently handle large model sizes. In this paper, we report on our implementation of the BIS using FLAME GPU, a parallel computing ABM simulator designed to execute on graphics processing units. To benchmark our implementation, we simulate the response of the immune system to a viral infection of generic tissue cells. We compared our results with those obtained from the original RePast implementation for statistical accuracy. We observe that our implementation has a 13× performance advantage over the original RePast implementation.


Author(s):  
D. A. Mills

In epidemiology, spatial and temporal variables are used to compute vaccination efficacy and effectiveness. The chosen resolution and scale of a spatial or spatio-temporal analysis will affect the results. When calculating vaccination efficacy, for example, a simple environment that offers various ideal outcomes is often modeled using coarse scale data aggregated on an annual basis. In contrast to the inadequacy of this aggregated method, this research uses agent based modeling of fine-scale neighborhood data centered around the interactions of infants in daycare and their families to demonstrate an accurate reflection of vaccination capabilities. Despite being able to prevent major symptoms, recent studies suggest that acellular Pertussis does not prevent the colonization and transmission of Bordetella Pertussis bacteria. After vaccination, a treated individual becomes a potential asymptomatic carrier of the Pertussis bacteria, rather than an immune individual. Agent based modeling enables the measurable depiction of asymptomatic carriers that are otherwise unaccounted for when calculating vaccination efficacy and effectiveness. Using empirical data from a Florida Pertussis outbreak case study, the results of this model demonstrate that asymptomatic carriers bias the calculated vaccination efficacy and reveal a need for reconsidering current methods that are widely used for calculating vaccination efficacy and effectiveness.


2014 ◽  
Vol 6 (4) ◽  
pp. 72-91
Author(s):  
Timothy W. C. Johnson ◽  
John R. Rankin

Large-scale Agent-Based Modelling and Simulation (ABMS) is a field of research that is becoming increasingly popular as researchers work to construct simulations at a higher level of complexity and realism than previously done. These systems can not only be difficult and time consuming to implement, but can also be constrained in their scope due to issues arising from a shortage of available processing power. This work simultaneously presents solutions to these two problems by demonstrating a model for ABMS that allows a developer to design their own simulation, which is then automatically converted into code capable of running on a mainstream Graphical Processing Unit (GPU). By harnessing the extra processing power afforded by the GPU this paper creates simulations that are capable of running in real-time with more autonomous agents than allowed by systems using traditional x86 processors.


Author(s):  
Nikola Vlahovic ◽  
Vlatko Ceric

Most economic and business systems are complex, dynamic, and nondeterministic systems. Different modeling techniques have been used for representing real life economic and business organizations either on a macro level (such as national economics) or micro level (such as business processes within a firm or strategies within an industry). Even though general computer simulation was used for modeling various systems (Zeigler, 1976) since the 1970s the limitation of computer resources did not allow for in-depth simulation of dynamic social phenomena. The dynamics of social systems and impact of the behavior of individual entities in social constructs were modeled using mathematical modeling or system dynamics. With the growing interest in multi agent systems that led to its standardization in the 1990s, multi agent systems were proposed for the use of modeling social systems (Gilbert & Conte, 1995). Multi agent simulation was able to provide a high level disintegration of the models and proper treatment of inhomogeneity and individualism of the agents, thus allowing for simulation of cooperation and competition. A number of simulation models were developed in the research of biological and ecological systems, such as models for testing the behavior and communication between social insects (bees and ants). Artificial systems for testing hypothesis about social order and norms, as well as ancient societies (Kohler, Gumerman, & Reynolds, 2005) were also simulated. Since then, agent-based modeling and simulation (ABMS) established itself as an attractive modeling technique (Klugl, 2001; Moss & Davidsson, 2001). Numerous software toolkits were released, such as Swarm, Repast, MASON and SeSAm. These toolkits make agent-based modeling easy enough to be attractive to practitioners from a variety of subject areas dealing with social interactions. They make agent-based modeling accessible to a large number of analysts with less programming experience.


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