Agent-Based
Computational Economics

Growing Economies from the Bottom Up

Last Updated: 8 January 2012

Site maintained by:
Leigh Tesfatsion
Professor of Econ, Math, and ECpE
Iowa State University
Ames, Iowa 50011-1070
http://www.econ.iastate.edu/tesfatsi/
tesfatsi AT iastate.edu

Scout Report for Business and Economics Selection
 ACE Logo

(Graphic by T. Eymann)

Table of Contents:




The Web http://www.econ.iastate.edu/tesfatsi/

Welcome to the ACE Website

Agent-based computational economics (ACE) is the computational study of economic processes modeled as dynamic systems of interacting agents. Here "agent" refers broadly to a bundle of data and behavioral methods representing an entity constituting part of a computationally constructed world.

Examples of possible agents include individuals (e.g. consumers, producers), social groupings (e.g. families, firms, communities, government agencies), institutions (e.g. markets, regulatory systems), biological entities (e.g. crops, livestock, forests), and physical entities (e.g. infrastructure, weather, and geographical regions). Thus, agents can range from active data-gathering decision makers with sophisticated learning capabilities to passive world features with no cognitive function. Moreover, agents can be composed of other agents, permitting hierarchical constructions.

Current ACE research divides roughly into four strands differentiated by objective.

One primary objective is empirical understanding: Why have particular observed regularities evolved and persisted despite the absence of top-down planning and control? Examples of such regularities include trade networks, socially accepted monies, market protocols, business cycles, and the common adoption of technological innovations. ACE researchers seek causal explanations grounded in the repeated interactions of agents operating in realistically rendered worlds. Specifically, they try to understand whether particular types of observed regularities can be reliably generated from particular types of agent-based worlds.

A second primary objective is normative understanding: How can ACE models be used as computational laboratories for the discovery of good economic designs? ACE researchers pursuing this objective are interested in evaluating whether designs proposed for economic policies, institutions, or processes will result in socially desirable system performance over time. The general approach is akin to filling a bucket with water to determine if it leaks. An agent-based world is constructed that captures the salient aspects of an economic system operating under the design. The world is then populated with privately motivated agents with learning capabilities and allowed to develop over time. One key issue is the extent to which the resulting world outcomes are efficient, fair, and orderly, despite attempts by agents to gain individual advantage through strategic behavior. A second key issue is a cautionary concern for adverse unintended consequences.

A third primary objective is qualitative insight and theory generation: How can ACE models be used to gain a better understanding of economic systems through a better understanding of their full range of potential behaviors over time (equilibria plus basins of attraction)? Such understanding would help to clarify not only why certain types of regularities have evolved and persisted but also why others have not. A quintessential example is the old but still unresolved concern of economists such as Adam Smith and Friedrich von Hayek: What are the self-organizing capabilities of decentralized market economies?

A fourth primary objective is methodological advancement: How best to provide ACE researchers with the methods and tools they need to undertake theoretical studies of economic systems through systematic computational experiments, and to examine the compatibility of experimentally-generated theories with real-world data? ACE researchers are exploring a variety of ways to address this objective ranging from careful consideration of methodological principles to the practical development of programming, visualization, and validation tools.

Linked below are materials of possible interest to ACE researchers in particular and more generally to social science researchers interested in the development and use of agent-based models. These materials are updated on a regular basis, and suggestions for additional materials to include are welcome.

In addition, ACE news notes are prepared as time permits and are posted at the ACE website. These ACE news notes provide a sample selection of pointers to new materials that have been included at the ACE Website since the last preparation of news notes. Whenever news notes are ready for posting, a brief announcement giving a pointer to this posting is emailed to all participants in a moderated Majordomo announcements-only ACE news list. Subscription to this moderated announcements-only news list is open to any interested readers.

If you would like to subscribe to (unsubscribe from) this moderated announcements-only ACE news list, please send an email message to majordomo@iastate.edu with the following message in the email body:
subscribe (unsubscribe) acenewslist youremailaddress
end
with your actual email address in place of youremailaddress. For more information, please visit the ACE News List Site

Please contact me at tesfatsi AT iastate.edu if you have ACE-related news items that you would like included at the ACE website and announced in the ACE news postings. Only items of persistent interest (e.g., not conference announcements) can be handled, and only batched postings by the moderator are permitted.

Thank you.

Materials Linked to Date

Introductory Materials on Agent-Based Social Science Modeling

Research Resources

Teaching Resources

Software Resources

News Items

Copyright © 2012 Leigh Tesfatsion. All Rights Reserved.