Agents in Complex Networks

Presented by Miguel Rebollo

Agent-based models are a promising area to deal with adaptive complex systems, which are characterized for a collective behavior that leads to emergent phenomena. Networks constitute a mathematical framework to study complex, emergent and self-organized environments, in which the relation among the participant entities plays a central role in the functioning of the community. The aim of this tutorial is to introduce the students in the area of complex networks. The tutorial will be divided in two parts. The first one will tackle the theoretical concepts regarding with the structure and the dynamics of the most known network models, scale-free and small-world phenomena. The second part is a practical one in which these models will be implemented using Netlogo.


  • Graphs
  • network models (random, growing network, preferential attachment)
  • network characterization (path length, clustering, centrality, assortativity)
  • network dynamics (search, diffusion, percolation, avalanches, synchronization)
  • applications (cooperative games, markets, networks in biology, social dynamics)

NOTE: If you have no previous experience programming in Netlogo and want to do this tutorial, although it is not mandatory, it is recommended to do also the “MAS Prototyping Tool: First Steps with Netlogo” tutorial Wednesday morning.