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A network model of knowledge accumulation through diffusion and upgrade

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In this paper, we introduce a model to describe knowledge accumulation through knowledge diffusion and knowledge upgrade in a multi-agent network. Here, knowledge diffusion refers to the distribution of existing knowledge in the network, while knowledge upgrade means the discovery of new knowledge. It is found that the population of the network and the number of each agent's neighbors affect the speed of knowledge accumulation. Four different policies for updating the neighboring agents are thus proposed, and their influence on the speed of knowledge accumulation and the topology evolution of the network are also studied. © 2011 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)2582-2592
JournalPhysica A: Statistical Mechanics and its Applications
Volume390
Issue number13
DOIs
Publication statusPublished - 1 Jul 2011

Research Keywords

  • Knowledge accumulation
  • Knowledge diffusion
  • Knowledge upgrade
  • Multi-agent network

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