I-700-ABMS, Agent-Based Modeling & Simluation, 2007-1

Instructors: Kristinn R. Thórisson, Rögnvaldur J. Sæmundsson
Teaching Assistant: Guðný R. Jónsdóttir
Technology: Ágúst Hlynur Hólmgeirsson
12 Units, full Master's-level course
Classroom: K4

• Introduction to Software Architecture, Garlan & Shaw - Main reading
• Constructionist Design Methodology (CDM) - Main reading
• CDM Paper, AI Magazine - Background material
• Allocative efficiency by Gode and Sunder 1993
• Standing Ovation Problem, Miller and Page 2004

• Comparative Econonomic Organization, Williamson 1991
• Can there be a science of complex systems? Herbert A. Simon

• Market
• Firms
• individuals, University, Jobcenter

This course provides students with theoretical and hands-on training in agent-based modeling techniques. Agent-based modeling is increasingly being used to understand activities and information flow in systems with goal-driven elements – systems such as social organizations, economies and the animal and human mind. Students will learn the basic elements of this advanced modeling approach and will gain experience in applying it to systems in two main areas: Economic organization of knowledge, and human thinking.

Being a methodology course, the material covered includes useful concepts and techniques from artificial intelligence that are generally applicable to modeling multi-layered, real-world systems; students interested in acquiring general-purpose skills for studying and simulating complex phenomena should find this an extremely valuable course, as should those interested in learning new approaches to understanding human thought and interpersonal knowledge transfer.

1. Programming experience recommended
2. A prior introductory class in one or more of the following is recommended: Artificial intelligence, Economic organization, Simulation techniques, Information science

Use the internal RU course website and CADIA SVN to return assignments. (Contact: GRJ,AHH)

Instructions for Gola

• Psyclone (5%); Emergence (5%); Economics (10%); Scaling (10%)

Counts 30% of final grade.
Students will give their group partner a grade, and each team will give the other teams a grade. The weight of student-given will be 50/50, and it will count for 50% of the mini-project grade against the instructors' grade. Group size: 2 (will be assigned randomly)

Final Project counts as 70% of final grade:

• Demonstration of runnable code (40%); Code documentation (10%); Final report (20%)

The students self-select for 2-person teams. Each team will be assigned an area to work on.

01 Tue 09: Introduction to course / Introduction to ABMS - KRTh | Readings: Intro to SW Arch; CDM
01 Thu 11: Introduction to CDM & Psyclone - KRTh, GRJ | Readings: Psyclone Manual | Psyclone Mini-Project - Assignment

02 Tue 16: Psyclone project walk-through (1hr)/ Introduction to Innovation and economic organization - KRTh/RJS Slides| Psyclone Mini-Project hand-in
02 Thu 18: Emergent behavior - RJS | Emergence Mini-Project - Assignment Slides

03 Tue 23: Emergent Behavior project walk-through (1hr) | Emergent Behavior Mini-Project hand-in | Economics Mini-Project - Assignment
03 Thu 25: Knowledge - KRTh | Basic principles of economics - RJS

04 Tue 30: Mini-project walk-through (1hr) | Economics Mini-Project hand-in | Scaling Mini-Project - Assignment

04 Thu 01: Learning, and ABM modelling techniques - KRTh

05 Tue 06: Scaling project walk-through (1hr)/Current model overview - KRTh/GRJ | Scaling Mini-Project hand-in
05 Thu 08: Final Project overview / Creation of groups - KRTh, RJS, GRJ

06 Tue 13: Setting up and experimenting with the current model - KRTh, RJS, GRJ
06 Thu 15: Lab.

07 Tue 20: Lab.
07 Thu 22: Lab.

08 Tue 27: Integration session 1 - KRTh, RJS, GRJ

08 Thu 01: Lab.

09 Tue 06: Lab.
09 Thu 08: Lab.

10 Tue 13: Integration session 2 - KRTh, RJS, GRJ
10 Thu 15: Lab.

11 Tue 20: Lab.
11 Thu 22: Lab.

12 Tue 27: Final integration session - KRTh, RJS, GRJ
12 Thu 29: Discussion and reflection on course - KRTh, RJS, GRJ