Individual-based models of collective dynamics in socio-economic systems

The purpose of this thesis is to contribute to the understanding of how complex collective behaviors emerge in social and economic systems. We use a combination of mathematical analysis and computational simulations within an agent- or individual-based modeling paradigm, thereby taking into account individual agents and their interactions. Our models are sufficiently simple in design to deepen the understanding of the mechanisms of emergence while being elaborate enough to lead to complex collective behaviors. In particular, we focus on three main topics: opinion dynamics,herding behavior in financial markets,and language competition.