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Agent-based Modeling

    Agent-based Opinion Dynamics

    The field of opinion dynamics, while studying the behaviour of systems with reactive agents, has been the one that more frequently reports on successful applications of concepts and techniques from dynamical systems theory. The role of structural interventions and their remarkable consequences to the system final states are at the root of the dynamics of opinion formation. In this topic we have been targeted at characterizing the interplay of opinion dynamics and the emergence of clusters of divergent opinions. From the network structure that underlies the dynamics of opinion exchange, we are able to show that when communication constraints are defined, the system is lead to a clustered opinion profile. A similar characterization addresses the role that existing (societal) structures play in the spread of innovation; and conversely, the effectiveness of innovation and its impact on structure creation in societies of agents.

    Agent based modelling of endogenous growth

    This is a relatively new framework that involves agent based modelling of endogenous growth economies with network effects. It's a contribution to interweave two lines of research that have progressed in a separated way: the endogenous, ideas based macroeconomic growth models, where the representative optimizing agent is the device that allows solving different allocation decisions, and the agents based economic literature, with a strong emphasis on heterogeneity and social interactions (social networks).
    Developing an agent model, where economic growth is a consequence of education (human capital formation) and innovation, we investigate the influence of the agents' social network, both on an agent's decision to pursue education and on the output of new ideas. Regular and random networks are considered. The results are compared with the predictions of a mean field (representative agent) model.