In a word, crowd network simulation is a new development of large scale simulations, which faces both opportunities and challenges. Member of crowd network simulations may need to achieve millions or even trillions so as to discover or verify its principals and regularities. Simulation is the main means to put forward related research studies.Ĭompared with traditional large-scale simulations, crowd network simulations have several obvious challenges as follows: However, because most results cannot be observed in real world, the research of crowd network cannot follow a traditional way. At the same time, with the rapid development of network technologies, crowd intelligence becomes much more complicate and universal, for human, enterprises, governments, equipments and articles turns to be more and more intelligent, and these intelligent agents are connecting to form numerous crowd network systems, such as e-commerce platforms, networked supply chains, Wikipedia and network elections ( Michelucci and Dickinson, 2016).Īs main mode of modern service industry and future economy society, the research on crowd network can greatly facilitate governances of economy society and make it more efficient, humane, sustainable and at the same time avoid disorders ( Chai et al., 2017).
#Anylogic software memory change full
The full terms of this licence may be seen at Īs the proverb goes “two heads are better than one” and “everybody’s business is nobody’s business”, the phenomenon of crowd intelligence can be easily observed in our daily lives. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Published in the International Journal of Crowd Science.
Ĭopyright © 2018, Sun Hongbo and Mi Zhang. (2018), "A reflective memory based framework for crowd network simulations", International Journal of Crowd Science, Vol. When developing new simulations, recompile is not necessary, which can acquire much more reusability, because reflective memory is adopted as share memory within given simulation execution in this framework population can be perceived by all federates, which greatly enhances the scalability of this kind of simulations communication efficiency and capability has greatly improved by this share memory-based framework.
Simulation syntax and semantic are all settled under this framework by templates, especially interface templates, as simulations are separated by two-level federations, physical and logical simulation environment are considered separately the definition of simulation execution is flexible.
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