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Emergence and Diffusion of Novel Associative Ideas in a Multi-Agent Network Model of Implicit Learning
Ist Teil von
Creativity and Innovation, 2021, p.229-264
Ort / Verlag
Switzerland: Springer International Publishing AG
Erscheinungsjahr
2021
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
The capacity of individuals to generate ideas depends crucially on the existing repertoire of their minds, and the exchange of ideas through social networks is a major mechanism for building this repertoire. From Granovetter’s discovery of the importance of weak ties to recent studies confirming the significance of strong ones, the ability of individuals to acquire information has been shown to depend strongly on their connectivity to others. Another important issue, however, is the role of cognitive factors—in particular, the value individuals place on the information they receive, their propensity to integrate it into their own knowledge base, and their ability to generate new information.
In this chapter, we introduce MANILA (Multi-Agent Network for the Implicit Learning of Associations)—a model simulating a network of cognitive, generative agents engaged in the implicit acquisition of associative knowledge through social interaction. In this context, implicit learning refers to agents acquiring new concepts and modifying conceptual associations by hearing about them from peers rather than by explicit instruction or active search. Arguably, such learning accounts for a large part of knowledge—correct and incorrect—that individuals acquire over their lifetimes, and which serves as the basis of their own ideation. We demonstrate the utility of MANILA by studying how the structure of the social network and the receptive preferences of agents affect the process of implicit knowledge acquisition and the ability of agent populations to generate novel conceptual combinations.