"Games and Agents" Workshop

Repository for the workshop materials @Conflict and Cooperation Laboratory, Leiden University. 13-16 June 2022

Ali Seyhun Saral (University of Bologna)
ali.saral@unibo.it

Schedule

13 June 2022, Monday

• 11:00-12:30 Session I
  • Introduction to ABM Slides
• 13:30-17:00 Session II
  • Python Crash Course Slides

14 June 2022, Tuesday

• 13:30-17:00 Session III
  • Python Classes Slides
  • Prisoner's Dilemma Matches Slides

15 June 2022, Wednesday

• 13:30-17:00 Session IV - Evolution & Agent-Based Simulations Slides
  • Axelrod Tournaments
  • Evolution of Prisoners Dilemma

16 June 2022, Thursday

• 13:30-17:00 Session V - ABM Frameworks, Grid Simulations & Advanced Topics Slides

Preparation

We are going to use Python for our simulations and Jupyter Notebook to have an interactive Python environment. If you are familiar with Python, you can use Python the way you'd like. But I suggest installing Jupyter Notebook at hand because I will give the exercises and notes in Jupyter Notebook Format (ipyb).

If you've never used Python, the easiest way to get Python and to run Jupyter Notebooks is by installing Anaconda. You should install the individual edition, which is free to use.

You can find the installers here: https://www.anaconda.com/products/distribution
You should use a Python 3 (for instance 3.9) version.

Although we will use it rarely, also it would be a plus to get familiarize running your operating system's command-line interface. In Windows, Command Line Prompt or Powershell can be used. In macOS and Linux, you have the Terminal.

After installing python and anaconda, you verify that they are installed properly by entering command line:

python --version

or

python3 --version

and

conda --version

You should be seeing something like Python 3.9.1 and Anaconda 4.4.10 depending on your version.

If you fail to install Anaconda, we will have some time before the second session starts. If you come to the second class 10-15 minutes earlier, I can help you install it. We will not use Python in the first session.

Prerequisites

There are no prequisites, but it would be helpful if you have some other programming tool experience. You don't really need to practice anything before the workshop, although if you'd like, you can take a look at Python basics. In the second (optional) session, we will cover Python basics anyways.

I will upload the slides and notes here shortly before each class.

Resources

Books

• Agent-Based and Individual-Based Modeling (NetLogo) - Steven F. Railsback Volker Grimm

• Introduction to Agent-Based Modelling (NetLogo)- Marco Janssen (https://intro2abm.com/)

• Individual-based models of cultural evolution. A step-by-step guide using R. - Alberto Acerbi, Alex Mesoudi, and Marco Smolla. (https://acerbialberto.com/IBM-cultevo/)

• Agent-Based Modeling for Archaeology: Simulating the Complexity of Societies (Netlogo) - Iza Romanowska, Colin D. Wren, Stefani A. Crabtree (https://www.sfipress.org/books/agent-based-modeling-archaeology)

• Spatial Simulation: Exploring Pattern and Process - David O'Sullivan and George L. W. Perry

• Fundementals of Multiagent Systems - Jose Vidal (https://jmvidal.cse.sc.edu/papers/mas.pdf)

Papers

• Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., ... & DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological modelling, 198(1-2), 115-126.

• Hamis, S., Stratiev, S., & Powathil, G. G. (2021). Uncertainty and sensitivity analyses methods for agent-based mathematical models: An introductory review. The Physics of Cancer: Research Advances, 1-37.

• Janssen, M. A. (2005). Agent-based modelling. Modelling in ecological economics, 155(1), 172-181.

• Axelrod, R., & Tesfatsion, L. (2006). Appendix AA guide for newcomers to agent-based modeling in the social sciences. Handbook of computational economics, 2, 1647-1659.

• Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the national academy of sciences, 99(suppl_3), 7280-7287.

• DeAngelis, D. L., & Grimm, V. (2014). Individual-based models in ecology after four decades. F1000prime reports, 6.

• Jackson, J. C., Rand, D., Lewis, K., Norton, M. I., & Gray, K. (2017). Agent-based modeling: A guide for social psychologists. Social Psychological and Personality Science, 8(4), 387-395.

E-Resources

• AgentPy Documentation: https://agentpy.readthedocs.io/en/latest/

• Mesa Documentation: https://mesa.readthedocs.io/en/latest/

• CoMSES Net Model Library: https://www.comses.net/codebases/

• NetLogo Model Library: https://ccl.northwestern.edu/netlogo/models/

Acknowledgements

• Thanks to Joël Foramitti for sharing the AgentPy workshop materials with me.