The study of small-world network knowledge transfer behavior model based on multi-agent simulation

Knowledge network is a typical social network, which is equipped with the feature of small-world. The paper adopts adaptive modeling method of Multi-Agent in complex adaptive system, applying Multi-Agent simulation platform Netlogo to construct the knowledge transfer simulation mode based on small-world net model. Using the average path length and clustering coefficient to stand for AC Frequency and Aggregation Degree among knowledge network nodes and studying the nodes´ ability to release and absorb as well as the knowledge transfer effect by trust degree. Operating simulation model means improving the AC Frequency and Aggregation Degree of nodes, enhancing nodes´ ability to transfer knowledge can ensure transfer frequency in organization reaching a high level and offer rules and guidance to construct net structure and behavior model suited with knowledge dissemination and transfer.