文档介绍：SOCIAL PUTER REVIEW
Johnson / AGENT-BASED MODELING
Agent-Based Modeling
What I Learned From the Artificial Stock Market
PAUL E. JOHNSON
University of Kansas
The Santa Fe Artificial Stock Market (ASM) is a well-known agent-based model. A new revision of the
code (ASM-) is now available. This article describes some of the changes that were made in the code
base and also presents some important lessons for agent-based modelers that can be illustrated with the
code. Because the code is available on the , it is hoped that this discussion and the code base it
represents will be helpful to people who are planning projects in the field of agent-based modeling.
Keywords: agent-based modeling, simulation, artificial stock market, object-oriented
programming, Swarm models
here is plenty of talk these days about “agent-based modeling” in social science, but
Tprecious little of it helps with the actual details of designing such a model and writing
code for it. This article explores some conclusions that were reached while working on a revi-
sion of the code for the Santa Fe Artificial Stock Market (ASM) model that was made famous
in a very widely cited article by R. G. Palmer, W. Brian Arthur, John H. Holland, Blake
LeBaron, and Paul Taylor (1994). The ASM was one of the first projects to demonstrate the
potential of agent-based models for the exploration of theories of decentralized, individual-
istic, and boundedly rational behavior. It has sparked a small cottage industry of research on
artificial stock markets (see LeBaron, 2000).
This article explores practical issues that any prospective model builder will confront.
These issues are of general importance, not just to people who want to write about stock mar-
kets or use a particular programming library. The overall message is that models should be
designed as separate, independently functional pieces of code (objects), and that some
guidelines can be followed to improve