Alex Makassiouk
ETH Zurich, D-MTEC, Chair of Systems Design
15.05.2024
This repository is dedicated to the exercises of the course Agent-Based Modeling of Economic Systems taught Spring 2024.
The course itself was taught by Prof. Dr. Frank Schweitzer (fschweitzer@ethz.ch), full professor for Systems Design at ETH Zurich since 2004. The exercises were organized and taught by Dr. Luca Verginer (lverginer@ethz.ch) and Dr. Giona Casiraghi (gcasiraghi@ethz.ch), both senior researchers at the chair of Systems Design. I want to thank them all and the class for a very interesting course and interesting, engaging discussions.
- Agent-Based Modeling Basics
- Random growth models
- Coupled growth and growth rate distributions
- Modeling entry and growth, data-driven modeling
- Models of entry and adoption, Polya Process
- Models of competition, Inequality
- Models of failure cascades, Systemic risk
- Selected PhD projects utilizing ABM
- Strategic network formation: Efficiency vs. stability
- Strategic network formation: Reciprocity
- Systems design: Network interventions
- Systems design: Induce cooperation
From exercise 4 and onward, Mesa was used as the ABM framework. It's an open-source Python library ideal for simulating complex systems.
- Python basics
- Random growth models - CLT, Bimodal mixture distribution, firm growth simulation
- Firm growth dynamics - Kesten model, Simulations with target size
- Yule-Simon distribution
- Polya Process and technology adoption - linear and nonlinear, preference- and technology utilities, lock-in effect
- Firm growth with interactivity - bilateral competition with firm in size proximity, transaction dynamics and resource exchange, parameter exploration
- Cascading processes on networks - Capacity, loads and failing nodes, inward and outward models
- No exercise 8
- Distance-based utility model - undirected network. sequential edge formation as best response for maximum utility
- Severance costs and leading eigenvalue utility - Introduction of severance costs to network formations.
- Network convergence and equilibria