Introduction to Computational Modeling of Social Systems

Transcription

1 Introduction to Computational Modeling of Social Systems Prof. Lars-Erik Cederman ETH - Center for Comparative and International Studies (CIS) Seilergraben 49, Room G.2, lcederman@ethz.ch Christa Deiwiks, CIS Room E.3, deiwiks@icr.gess.ethz.ch Week 1

2 Today s agenda 2 Introduction Course goals Course contents Course logistics Prerequisites and grading Schedule WebCT teaching system Examplesof agent-based models Simple models: Schelling, Traffic, AIDS, Sugarscape Complex models: Anasazi, Geosim

3 Course goals 3 Become familiar with the paradigm Advance your programming skills 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 4 Short Java Primer Introduction to the principles of agentbased modeling Introduction to RePast modeling In SS 2007 there will be an advanced course extending this introductory lecture

5 Course logistics 5 Prerequisites: Programming experience (preferably in an object-oriented language) Grading: Four sets of exercises To be completed through the WebCT online teaching system Resources: Course web page where you ll find the link to WebCT:

6 The WebCT online teaching system 6

7 Course schedule 7 October 24: Introduction Examples of agent-based models in the social sciences October 31: Java Primer / Gearing up November 7: Principles of agent-based modeling November 14: A hand-crafted agent-based model November 21: The Iterated Prisoner s Dilemma and RePast Tutorial I November 28: RePast Tutorial II December 5: RePast Tutorial III December 12: RePast Tutorial IV December 19: Emergent Network models January 9: Emergent Structure models January 16: Emergent Actor models, GeoContest January 23: Emergent Actor models II January 30: Emergent Actor models III, GeoContest Presentation

8 What is agent-based modeling? 8 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

9 Disaggregated modeling 9 If If <cond> then <action1> else <action2> Animate agents Inanimate agents Observer Organizations of agents Artificial world Data

10 Java 10 Conceived by Sun in the early 1990s Became the new standard for the web thanks to platform-independence C syntax syntax C++ object model

11 Modeling in RePast 11 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

12 RePast framework 12 Controlling simulations Displaying behavior Charting Managing parameters

13 General readings on agent-based modeling 13 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 Simple sample models Schelling s segregation model RePast 2. Traffic simulation NetLogo 3. AIDS NetLogo

15 Example 1: Neighborhood segregation 15 Micro-level rules of the game Stay if at least a third of neighbors are kin < 1/3 Move to random location otherwise Thomas C. Schelling Micromotives and Macrobehavior

16 Example 2: Traffic simulation (NetLogo) 16 Model of the movement of cars on a highway Each car follows a simple set of rules: if there s car close ahead, it slows down if there s no car ahead, it speeds up The project demonstrates how traffic jams form spontaneously without obstacles

17 Example 3: AIDS (NetLogo) 17 Simulate the spread of the human immunodeficiency virus (HIV), via sexual transmission Control of the population's tendency to practice abstinence amount of time an average "couple" in the population will stay together population's tendency to use condoms population's tendency to get tested for HIV

18 Complex sample models Anasazi village formation 2. Nationalist insurgencies in Geosim

19 Example 1: Anasazi Village Formation 19 Gumerman et al SFI Working Paper (among others) Reconstruction of settlement patterns and demographics of pueblo Indians in the American Southwest The main puzzle pertains to the group s sudden disappearance Based on the Sugarscape model, and thus also programmed in Ascape

20 Example 2: Geosim 20 Geopolitical simulation system Cederman (2004) Articulating the Mechanisms of Nationalist Insurgencies Based on RePast 3##44#2# National identities Cultural map State system Territorial obstacles

21 Where to find more models: Links 21 See Resources under class home page Santa Fe Institute: Center for the Study of Complex Systems at the University of Michigan: European web sites on Computer simulation of societies and European Social Simulation Association For the US counterpart, see Leigh Tesfatsions s site on computational economics: See also the Journal of Artificial Societies and Social Simulation: