This chapter focuses on three questions: what norms are, how they emerge, and how much and what type of mental complexity they need; and the chapter presents a dynamic model of norms and the corresponding agent architecture (EMIL-A), and shows the results of its application to a stylized environment (a social multi-setting world). The chapter then illustrates a simulator, EMIL-S, on which EMIL-A has fully been implemented, showes its effects on the emergence of a new norm in a more complex artificial context (artificial Wikipedia), and compares the results with data from a survey on the real-world domain of reference (Wikipedia). This chapter describes EMIL-I-A (EMIL Internalizer Agent), an extension of EMIL-A designed to account for a deeper form of norm immergence than addressed so far; i.e., norm internalization. Then it presents simulation results aimed at testing how EMIL-I-A performs in dynamic, unpredictable scenarios.
The Role of Norm Internalizers in Mixed Populations
Contributo in volume
Minding Norms. Mechanisms and dynamics of social order in agent societies, edited by Conte, R., Andrighetto, G., Campennì, M., pp. 153â€“170, 2013
info:cnr-pdr/source/autori:Andrighetto, R. Villatoro, D., G., Conte/titolo:The Role of Norm Internalizers in Mixed Populations/titolo_volume:Minding Norms. Mechanisms and dynamics of social order in agent societies/curatori_volume:Conte, R., Andrighetto,