@article{noronha_simulating_2013,
	title = {Simulating the {Diffusion} of {Innovation} {Process} a {Multi} {Agent} {Approach}},
	copyright = {Creative Commons Attribution 4.0 International},
	url = {https://figshare.com/articles/conference_contribution/Simulating_the_Diffusion_of_Innovation_Process_a_Multi_Agent_Approach/16825831/1},
	doi = {10.6084/M9.FIGSHARE.16825831.V1},
	abstract = {Multi-agent based simulations provide tools andtechniques to observe and analyze the emergentbehavior that happens due to the interactions amongagents. These agents could represent the actors in a realsituation, or they could be used to test or to verifyhypothesis, theories and to perform experiments in acontrolled environment (e.g. virtual world). It is usefulin certain cases, for instance when the event and itsinner workings are hard to observe, which is common insocial simulations. The diffusion of innovation theory,presented by Everett Rogers, provides a classification ofthe individuals in a social system related to how long aninnovation takes to spread into the system. Also, itdescribes how people form clusters based on thehomophily concept. This paper brings two hypothesesfor the diffusion of innovation and puts them into testby a multi-agent based simulation, running in theSwarm multi-agent based framework. Rogers’ theory,as well as multi-agent based simulations, is brieflypresented so they become a background for thepresented model. Also, the simulation and its results areshown. Finally, conclusions and future works arediscussed.},
	urldate = {2024-01-23},
	author = {Noronha, Emerson and Lima Ruas, Terry and Marietto, Maria das Graças Bruno and Steinberger-Elias, Margarethe and Botelho, Wagner Tanaka and França, Robson dos Santos and Soares, Camila},
	year = {2013},
	note = {Artwork Size: 424158 Bytes
Publisher: figshare},
	keywords = {80110 Simulation and Modelling, FOS: Computer and information sciences},
	pages = {424158 Bytes},
}

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