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2017/2018 Technology, Policy and Management Master Complex Systems Engineering and Management
Agent-based Modelling
Module Manager
Name E-mail
Dr.ir. I. Nikolic    I.Nikolic@tudelft.nl
Name E-mail
Dr.ir. I. Nikolic    I.Nikolic@tudelft.nl
Dr. M.E. Warnier    M.E.Warnier@tudelft.nl
Responsible for assignments
Name E-mail
Dr.ir. I. Nikolic    I.Nikolic@tudelft.nl
Co-responsible for assignments
Name E-mail
Dr. M.E. Warnier    M.E.Warnier@tudelft.nl
Contact Hours / Week x/x/x/x
Education Period
Start Education
Exam Period
Course Language
Course Contents
Our human society consists of many intertwined Large Scale Socio-Technical Systems (LSSTS), such as infrastructures, industrial networks, the financial and legal systems etc. Environmental pressures created by these systems on Earth's carrying capacity are leading to exhaustion of natural resources, loss of habitats and biodiversity, and are causing a resource and climate crisis. To avoid this sustainability crisis, we urgently need to transform our production and consumption patterns. Given that we, as inhabitants of this planet, are part of a complex and integrated global system where and how should we begin this transformation? And how can we also ensure that our transformation efforts will lead to a sustainable world?

LSSTS and the ecosystems that they are embedded in are known to be Complex Adaptive Systems (CAS). According to John Holland CAS are "...a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it will have to to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment" by many individual agents.

Understanding Complex Adaptive Systems requires tools that themselves are complex to create and understand. Shalizi defines Agent Based Modeling as "An agent is a persistent thing which has some state we find worth representing, and which interacts with other agents, mutually modifying each others states. The components of an agent-based model are a collection of agents and their states, the rules governing the interactions of the agents and the environment within which they live."

This course will explore the theory of CAS and their main properties. It will also teach you how to work with Agent Based Models in order to model and understand CAS.
Study Goals
The two goal of the course are, first, to understand Complex Adaptive Systems theory and its relation to the socio-technical systems around us. Second goal is for the student to learn about the the basics of Agent Based Modeling.

More formally, there are 5 course goals:
1. Students should know the definitions of CAS properties, as listed in the course topics
2. Students should be able to identify relevant properties of a system and determine whether or not the system can be classified as CAS.
3. Students should be able to create a coherent description of a system from both top down and bottom up
4. Students should be able to understand and modify and create Agent Based Simulations in NetLogo.
5. Students should be able to reflect on the traditional engineering systems thinking from the CAS perspective and understand the implications of changing the traditional perspective.
Education Method
Course consists of a series of lectures and practicals and a final modeling project.

Lectures and practicals are intertwined, building on top of each other. Where possible, the theory discussed in the lectures will be explored in a practical. Lectures will explore the interrelated properties of complex systems.

The practicals are meant to teach you to work with NetLogo and experience the CAS properties discussed during the lectures. The practicals build up in complexity, and once we reach a sufficient proficiency with NetLogo, we will move on to the modeling project.

Modeling project
The second part of the course is dedicated to creating a model in small teams, applying the skills learned during the practicals. The project deliverable consists of the simulation code and report documenting the problem statement, model design, performed experiments and data analysis. This is a compulsory project, contributing 50% to the final grade.
Computer Use
The course involves developing and experiment with simulations in NetLogo.
The final grade of the course is based 50% on the written exam and 50% on the modeling project(simulation + report). Both parts must be completed with a passing grade (at least 5.75) in order to pass the course. A partial grade for the written exam or modeling project is only valid within the same academic year. You can not compensate with a partial grade from previous year. If you do not pass both parts within the same academic year, you will have to retake the entire course.