By Quan Bai, Fenghui Ren, Minjie Zhang, Takayuki Ito, Xijin Tang
This ebook goals to supply an outline of those new synthetic Intelligence applied sciences and techniques to the modeling and simulation of advanced structures, in addition to an summary of the most recent medical efforts during this box akin to the structures and/or the software program instruments for clever modeling and simulating advanced structures. those initiatives are tough to complete utilizing conventional computational methods as a result of the complicated relationships of parts and dispensed good points of assets, in addition to the dynamic paintings environments. so that it will successfully version the complicated structures, clever applied sciences similar to multi-agent platforms and shrewdpermanent grids are hired to version and simulate the complicated structures within the parts of atmosphere, social and fiscal association, web-based grid carrier, transportation platforms, energy structures and evacuation systems.
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Extra info for Smart Modeling and Simulation for Complex Systems: Practice and Theory
The group formation mechanism is conducted based on an iteration process. The group formation mechanism is described by Algorithm 1. e. NNC is set to the number of neighbours of Aj (since Aj is the coordinator of itself) (see line 2). g. Aj ) repeats the following three steps. g. e. g. C). If a different coordinator 46 X. Su et al. NNC (see lines 8–9). The above three steps (lines 4–9) will be repeated by each agent until no further updating for three variables of any agent. 3 Token Passing In this step, each agent Aj first gets task tokens (see Definition 3) and agent tokens (see Definition 4) (created in the task token creation step) from its child agents.
6 Motivation The motivation module provides a mechanism for peeps to interact with each other and their environment. The module allows peeps to have variables (called characteristics), which can be influenced by other peeps and the environment. Peeps may also have one or more if-then-else rules, which can execute actions. The values of a peep’s characteristics determine which rules (and hence, actions) are executed. This has been used, for example, to model the spread of panic through a population.
Our results suggest that location of release is a significant factor in determining the number of subsequent infections. This is hardly surprising given that different locations will have greatly varying traffic levels and patterns. Such simulations could be of interest for the purposes of risk assessment, provisioning resources to cope with an attack, and the effectiveness of potential interventions. The second scenario examined the effectiveness of a simple interdiction strategy against terrorist activity.