Application Of Agent-Based Multimethod Simulation Approach To The Simulation Testbed Prototype For The Concept Exploration And Requirement Analysis Of UGV

Author(s):  
Sang Yeong Choi ◽  
Kang Park ◽  
Ji Hyun Yang ◽  
Hwan II Kang
2010 ◽  
Vol 92 (4) ◽  
pp. 309-320 ◽  
Author(s):  
EDSON SANDOVAL-CASTELLANOS

SummaryAnalysis of the temporal variation in allele frequencies is useful for studying microevolutionary processes. However, many statistical methods routinely used to test temporal changes in allele frequencies fail to establish a proper hypothesis or have theoretical or practical limitations. Here, a Bayesian statistical test is proposed in which the distribution of the distances among sampling frequencies is approached with computer simulations, and hypergeometric sampling is considered instead of binomial sampling. To validate the test and compare its performance with other tests, agent-based model simulations were run for a variety of scenarios, and two real molecular databases were analysed. The results showed that the simulation test (ST) maintained the significance value used (α=0·05) for a vast combination of parameter values, whereas other tests were sensitive to the effect of genetic drift or binomial sampling. The differences between binomial and hypergeometric sampling were more complex than expected, and a novel effect was described. This study suggests that the ST is especially useful for studies with small populations and many alleles, as in microsatellite or sequencing molecular data.


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):  
Marijn Janssen ◽  
Henk G. Sol

Developments in Information and Communication Technology (ICT) enable information systems to intermediate between sellers and buyers in electronic markets (e-markets). A business engineering methodology can be of help to design and develop e-markets by providing insight into current market and potential e-market structures, matching mechanisms and processes, and by evaluating the implications of e-markets. In this chapter, a first concept of an interactive, discrete-event, agent-based simulation approach for the analyses and design of e-markets is presented and evaluated.


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