Computational Economics

Growing Economies from the Bottom Up

Last Updated: 20 July 2015

Site maintained by:
Leigh Tesfatsion
Professor of Econ, Math, and ECpE
Iowa State University
Ames, Iowa 50011-1070
tesfatsi AT

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Table of Contents:

The Web

Welcome to the ACE Website

Agent-based computational economics (ACE) is the computational modeling of economic processes (including whole economies) as open-ended dynamic systems of interacting agents.

Here "agent" refers broadly to a bundle of data and methods representing an entity residing within the system. Examples of agents include individuals (e.g., family farmer, city resident), social groupings (e.g., families, communities, NGOs), institutions (e.g., corporations, markets, legal and regulatory systems), biological entities (e.g., crops, livestock), and physical entities (e.g., river, land regions, weather, transport networks). Thus, agents can range from passive system features to active data-gathering decision-makers capable of sophisticated learning and social behaviors. Moreover, agents can be composed of other agents, permitting hierarchical constructions.

ACE models are computational laboratories permitting users to explore how changes in structural conditions, institutional arrangements, and/or human decision processes affect system outcomes over time. This exploration process is similar to biological experimentation with cultures in petri dishes. A user sets initial system conditions as desired for some purpose at hand. The system "cover" is then closed, and the system thereafter runs forward through time as an autonomous virtual world whose dynamics are driven entirely by the actions and interactions of its constituent agents. No resort to externally imposed sky-hooks enforcing global coordination, such as modeler-imposed market clearing and rational expectations constraints, should be needed to drive or support the dynamics of this world.

Important Note: A major misconception, still being expressed by some mainstream economists and bloggers uninformed about the powerful capabilities of modern software, is that ACE decision-making agents cannot exhibit forward-looking behavior. To the contrary, as demonstrated concretely in this study, the locally-constructive decision procedures used by ACE agents can range from simple behavioral rules to sophisticated adaptive dynamic programming methods for the approximate achievement of intertemporal objectives. Extensive annotated pointers to reference materials on the implementation of learning methods for ACE agents can be accessed at the following site: ACE Research Area: Learning and the Embodied Mind.

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 virtual worlds. Specifically, they try to understand whether particular types of observed regularities can be reliably generated within these 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. A virtual 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 dynamic 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 dynamic 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 as well as to researchers more generally who wish to explore the potential usefulness of agent-based modeling for social science purposes. These materials are updated on a regular basis, and suggestions for additional materials to include are welcome.

As time permits, ACE news notes are posted below to let people know which ACE Website pages have been most heavily updated since the last news notes posting. Whenever these 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 with the following message in the email body:
subscribe (unsubscribe) acenewslist youremailaddress
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 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

Teaching Resources

Software Resources

Research Area Sites

Other Research Resources

News Items

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