We study an agent-based model, as a special type of opinion dynamics, of the spreading
of innovations in socio-economic systems varying the topology of agents’ social
contacts. The agents are organized on a square lattice where the connections are
rewired with a certain probability. We show that the degree polydispersity and
long range connections of agents can facilitate, but can also hinder the spreading
of new technologies, depending on the amount of advantages provided by the
innovation. We determine the critical fraction of innovative agents required to initiate
spreading and to obtain a significant technological progress. As the fraction of
innovative agents approaches the critical value, the spreading process slows down
analogously to the critical slowing down observed at continuous phase transitions. The
characteristic timescale at the critical point proved to have the same scaling as the
average shortest path of the underlying social network. The model captures some
relevant features of the spreading of innovations in telecommunication technologies.
We introduce an agent-based model for the spreading of technological developments in socio-economic systems where the technology is mainly used for the collaboration/interaction of agents. Agents use products of different technologies to collaborate with each other which induce costs proportional to the difference of technological levels. Additional costs arise when technologies of different providers are used. Agents can adopt technologies and providers of their interacting partners in order to reduce their costs leading to microscopic rearrangements of the system. Analytical calculations and computer simulations revealed that starting from a random configuration of different technological levels a complex time evolution emerges where the spreading of advanced technologies and the overall technological progress of the system are determined by the amount of advantages more advanced technologies provide, and by the structure of the social environment of agents. We show that agents tend to form clusters of identical technological level with a power law size distribution. When technological progress arises, the spreading of technologies in the system can be described by extreme order statistics.
We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.
Abstract-We propose a method of generating different scalefree networks, which has several input parameters in order to adjust the structure, so that they can serve as a basis for computer simulation of real-world phenomena. The topological structure of these networks was studied to determine what kind of networks can be produced and how can we give the appropriate values of parameters to get a desired structure.amely az rzkels, rzet, megismers s megrts kztt zajl agyi folyamatok mrnki informatikai modellezse
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