Agent-based modeling is introduced as a bottom-up approach to understand the complex dynamics of social systems. Topics include the growth, entry and exit dynamics of firms, strategic interactions of firms in collaboration networks and the emergence of failure cascades and systemic risk in networks. The role of randomness, heterogeneity and network effects for economic dynamics is pointed out.

The course provides an overview of the methods and abstractions used in (i) the quantitative study of complex networks, (ii) empirical network analysis, (iii) the study of dynamical processes in networked systems, (iv) the analysis of robustness of networked systems, (v) the study of network evolution, and (vi) data mining techniques for networked data sets.

This module is an addition to the course Systems Dynamics and Complexity. It offers additional study cases to MAVT Bachelor students who enroll in the main course.