VII Trento Summer School

Agent-Based Computational Economics (ACE):
Growing Economies from the Bottom Up

Supporting Materials for
Lectures by Co-Director Leigh Tesfatsion

Last Updated: 23 July 2006

Co-Director Contact Information:
Leigh Tesfatsion
http://www.econ.iastate.edu/tesfatsi/
tesfatsi AT iastate.edu

Exercise Info
Course Project Info
ACE Website
ACE Demo Software
RepastJ Guide (Agent-Based Modeling Toolkit)
ACE Course (Self-Study eBook)
Course Overview
Topics, Readings, & Exercises


The Web http://www.econ.iastate.edu/classes/econ308/tesfatsion/

Course Overview

A modern market-based economy is a complex adaptive system. Vast numbers of geographically-distributed individuals and social groupings interact over time through markets and other institutions. They struggle to survive and, if possible, to prosper, by learning how to compete and cooperate in appropriate measure. These micro interactions give rise to regularities at the level of society as a whole, such as trade networks, socially accepted monies, and the common adoption of technological innovations. In turn, social regularities feed back into the determination of micro interactions.

Recent developments in computer modeling, in particular object-oriented and agent-oriented programming tools, permit new approaches to the study of this complex two-way feedback between micro interactions and social regularities. The primary objective of this intensive course is to introduce, motivate, and explore through concrete applications the potential usefulness of one such approach -- Agent-based Computational Economics (ACE) -- the computational study of economic processes modeled as dynamic systems of interacting agents.

Topics, Readings, and Exercise Assignments

PLEASE NOTE:

Required readings are marked below with two asterisks (**). Highly recommended readings are listed with a single asterisk (*) and other recommended are listed with no asterisk.

  1. Introduction
    1. What are Complex Adaptive Systems (CAS)?
    2. What is ACE?
  2. The Complexity of Decentralized Market Economies
  3. Design and Use of Computational Laboratories
  4. Learning and the Embodied Mind
    1. Illustrative Examples of Situated Learning
    2. Learning Representations
  5. Financial Market Illustrations
  6. Economic Interaction on Fixed Networks
  7. Endogenous Network Formation: Labor Market Illustration
  8. Real-World Application: Electricity Restructuring Project
  9. Empirical Validation of ACE Models

Appendix: Possible Course Project Topic Areas (with Linked Resource Sites)

I. Introduction

I.A What are Complex Adaptive Systems (CAS)?

Key In-Class Discussion Topics:

** Exercise 1 (Team Exercise): Introduction to the Schelling Segregation Model (pdf,27K).

** Exercise 2 (Team Exercise): Conducting Experiments with Chris Cook's Schelling Demo Model (pdf,27K).

Required Readings:

Recommended Materials:

I.B What is Agent-based Computational Economics (ACE)?

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other introductory source materials on CAS/ACE

II. Complexity of Decentralized Market Economies

Key In-Class Discussion Topics:

** Exercise 3 (Team Exercise): Construction and Analysis of Market Demand and Supply Functions (pdf,25K).

** Exercise 4 (Team Exercise): Game Theory Analysis of Strategic Market Pricing, (pdf,45K).

Required Readings:

Recommended Materials:

ACE-Related Research on Multi-Market Modeling

III. Design and Use of Computational Laboratories

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other source materials related to computational laboratories

IV. Learning and the Embodied Mind

IV.A Illustrative Examples of Situated Learning

Key In-Class Discussion Topics:

** In-Class Experiment: So how do YOU play the IPD?

** In-Class Experiment: One for all and all for one -- maybe!

** Exercise 5 (Team Exercise): Conducting Experiments with Chris Cook's Axelrod Tournament Demo, (pdf,39K).

Required Readings:

Recommended Materials:

IV.B Learning Representations

Key In-Class Discussion Topics:

In-Class Exercise

** Exercise 6 (Team Exercise): Conducting Genetic Algorithm Learning Experiments with the Trade Network Game (TNG) Laboratory (pdf,48K).

Required Readings:

Recommended Materials:

Other source materials related to learning

V. Financial Market Illustrations

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other source materials related to ACE financial modeling

VI. Economic Interaction on Fixed Networks

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other source materials related to ACE network research

VII. Endogenous Network Formation: Labor Market Illustration

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other source materials ACE labor research

General resource site on network formation

VIII. Real-World Application: Electricity Restructuring Project

Key In-Class Discussion Topics:

Required Readings:

Other source materials on ACE electricity research

General resources on electricity restructuring

IX. Empirical Validation of ACE Models

Key In-Class Discussion Topics:

Required Readings:

Recommended Materials:

Other source materials on the empirical validation of ACE models

Appendix: Possible Course Project Topic Areas
(with Linked Resource Sites)

Important Note: Participants in the VII Trento Summer School are strongly encouraged to begin consideration of possible course project topics as soon as possible. Please visit the Course Project Information Site for more detailed information regarding course projects, including a list of course projects selected by students in my ACE course (Econ 308) at Iowa State University in previous years. For those wishing to explore course project topics not included at this site, a more general collection of possible topic areas (with linked resource sites) is provided below.

Copyright © 2006 Leigh Tesfatsion. All Rights Reserved.