Prof. Lars-Erik Cederman ETH - Center for Comparative and International Studies (CIS) Seilergraben 49, Room G.2, Nils Weidmann, CIS Room E.3, Introduction to Computational Modeling of Social Systems

2 Today’s agenda Introduction –Course goals –Course contents –Examples Course logistics –Prerequisites and grading –Schedule –Hardware requirements

3 Course goals Become familiar with the paradigm Learn programming in Java Master RePast libraries Construct a simple computational model Start to think about how to apply the method to your own research puzzle

4 Course contents Introduction to the principles of agent- based modeling Introduction to Java programming Introduction to RePast modeling In SS 2005 there will be an advanced course extending this introductory lecture

5 What is agent-based modeling? ABM is a computational methodology that allows the analyst to create, analyze, and experiment with, artificial worlds populated by agents that interact in non-trivial ways Different from other types of computational techniques: econometrics, numerical solution, global modeling, AI modeling

6 Disaggregated modeling Organizations of agents Animate agents Data Artificial world Observer Inanimate agents If then else If then else

7 Example: Iterated prisoner's dilemma Generations of agents are pitted against each other in an interaction topology Each game involves two agents that make iterated, simultaneous choices Strategies evolve over time, from generation to generation

8 Conceived by Sun in the early 1990s Became the new standard for the web thanks to platform-independence Java C C++ syntax object model

9 Modeling in RePast “Recursive Porous Agent Simulation Toolkit” RePast is an open-source software framework for creating agent-based simulations using the Java programming language Initially developed by the Social Science Research Computing at the University of Chicago since January 2000: Modeled on Swarm but easier to use and better documented

10 RePast framework Controlling simulations Displaying behavior Charting Managing parameters

11 Course logistics Prerequisites: No programming experience needed but obviously helpful Grading: –Four sets of exercises –Final tournament Resources: –Course web page

12 Readings on Java Eckel, Bruce Thinking in Java. Upper Saddle River, NJ: Prentice Hall. See also: Schildt, Herbert Java 2: A Beginner’s Guide. Osborne McGraw Hill. See also Sun’s Java Tutorial:

13 General readings on agent- based modeling Axelrod, Robert The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton: Princeton University Press. Casti, John L Would-Be Worlds: How Simulation Is Changing the Frontiers of Science. New York: Wiley. Cederman, Lars-Erik Emergent Actors in World Politics: How States and Nations Develop and Dissolve. Princeton: Princeton University Press. Epstein, Joshua M. and Robert Axtell Growing Artificial Societies: Social Science From the Bottom Up. Cambridge, Mass.: MIT Press. Holland, John H Hidden Order: How Adaptation Builds Complexity. Reading, Mass.: Addison-Wesley.

14 Course schedule October 19: Introduction October 26: Examples of agent-based models in the social sciences November 2: The principles of agent-based modeling November 9: Java Primer I November 16: Java Primer II November 23:Java Primer III November 30:A hand-crafted agent-based model December 7:Introduction to the Iterated Prisoner’s Dilemma December 14: RePast Introduction and Tutorial I December 21: RePast Tutorial II January 11: RePast Tutorial III January 18: Emergent-structure models January 25: Emergent-network models February 1: Emergent-actor models February 8: TBA

15 Gearing up Hardware –Windows computer with Pentium II, 400MHz, 256MB RAM, 150MB disk space or –Macintosh running OS X or –Linux / Unix Software (all free!) –Java –RePast –IntelliJ IDEA (or other development environment) –Installation guide (see link to Models on class web page)!