CS382:Unit-compsoc

Computational Sociology with Agent Based Modeling

Background reading, one or more pointers/documents and a brief synopsis of what's covered in them

You're missing the synopses on what these are about.

• Computational Sociology (wikipedia)
• The Structural Dynamics of Corruption: Artificial Society Approach - I have concerns about whether freshmen students will be able to sit down and read this. This might be interesting to cover but as part of the lecture.
• Macro And Micro Dynamics In An Artificial Society: An Agent Based Approach - This link is broken
• Artificial Societies, Virtual Worlds and the Shared Problems and Possibilities of Emergence - Not really sure how this fits in with modeling computational sociology, because these are player-controlled
• Journal of Artificial Societies and Social Simulation - A list of articles isn't very helpful. Sorry. It's still a resource for background reading.
• Growing Artificial Societies: Social Science From the Bottom Up (book citation) This is an entire book. For students to read for this unit?
• Tutorial on Agent Based Modeling ACM Digital Library
• Computational Sociology and Agent Based Modeling - This is interesting but very long. Students are really going to sit down and read forty pages about something they don't know much about?

Lecture notes - outline form

• What is Agent Based Modeling?
  • Game of Life
  • Emergent Behavior
  • Axtell and Epstein - Growing Artificial Societies
  • What are its advantages and disadvantages?
• Where is it useful?
  • Economics
  • Sociology
  • Biology
  • Information Science
• Some Examples
  • Boids
  • Self Assembling of Information on networks
  • Sugarscape
• Is the focus of this unit computational sociology or agent-based modeling? The reading makes it out to be computational sociology but the lecture is far more agent-based modeling.
  • leave what i have here, expand for computational sociology

Classroom response questions - at least three

• 1. What is Emergent Behavior?
  • A. The complex outcome of the interaction of many simple rulesets
  • B. How we verify and validate Agent Based models
  • C. How we define rulesets for agents in an agent based model
  • D. How we determine the formulas we use in mathematical modeling
• 2. Who wrote the seminal text on sociological agent-based modeling?
  • A. Peck & Rogers, et. al
  • B. Axtell and Epstein
  • C. Axeman and Edlefsen
  • D. Whitehall and North
• 3. What is the name of the first agent-based biological model?
  • A. Droids
  • B. BirdBots
  • C. Boids
  • D. BDroids

Lab activity - materials, process and software

Self Assembling of Information on networks

Tie this in with facebook/myspace/<social network here (virtual or real)>. Who do you know? Draw a graph of your best friends, good friends, acquaintances, less-than-acquaintances and follow the coloring/sizing of the model. Does this model resemble what emerges in the dynamic model? Do several runs of the model and match their emergent stages against your drawing. Discuss validity of model based on this.

• Model

I like the idea of using students' own social networks and getting them involved with that, but I'm not entirely sure what you mean about them drawing the model. Their drawing would be flat, whereas the model is constantly changing with information being moved around. How does information move in the students' drawing?

• The key for the lab is "Does this model resemble what emerges in the dynamic model?" The applet will run until it reaches a state of relative stasis. The static model that the students develop will, hopefully, have similar characteristics to the applet's emerged results. The idea is that 'reality' - the static model - appears in the emergent behavior of the dynamic model.

Scheduling - early, late, dependencies on other units, length of unit

Timing

Should certainly come after mathematical modeling. Other than that I don't think it matters.

Length

Two weeks. It's important and there's a lot of good stuff to do.

Gen Ed

Criterion 1

Develops students' understanding of the natural world.

• Unit develops students' ability to understand the natural world as a chaotic - but emergent - system.

Criterion 2

Strengthens students' knowledge of the scientific way of knowing — the use of systematic observation and experimentation to develop theories and test hypotheses.

• The lab requires the collection of data first-hand and its comparison to the results of a model. I'd say this nail is hit on the head.

Criterion 3

Emphasizes and provides first-hand experience with both theoretical analysis and the collection of empirical data.

• The collection of empirical data: coming up with static models and, in a possible second lab, determining simple rulesets of some agentset. Theoretical analysis: all the models students interact with in the unit.

Archived stuff

• brian castellani sociology and complexity web
  • Modeling social mobility. Paper, too
• Center for Models of Life - CMOL: Models / Interactive Java Applets
  • A model of information and dominance, Related paper
  • Modeling self organization of communication and topology in social networks