!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> Streamline Training & Documentation: When to Consider Agent-Based Modeling

Tuesday, February 09, 2010

When to Consider Agent-Based Modeling

As a follow-on to yesterday's post about using agent-based simulation to model the economy, I'd like to suggest that the technically minded have a look at a paper (pdf) Charles M. Macal and Michael J. North, both at Argonne National Laboratory, presented at the 2009 Winter Simulation Conference.

The paper discusses both how to think about agent-based modeling and simulation (ABMS), and how to actually do ABMS. The latter portion of the paper includes guidance on software and toolkits specially designed for ABMS.

Even the non-technically minded can benefit from reading through Macal and North's list of criteria for considering an agent-based approach to simulating a dynamic system. The eleven criteria — any one of which is sufficient to suggest an agent-based approach — are:
  1. The problem has a natural representation as being comprised of agents

  2. There are decisions and behaviors that can be well-defined.

  3. It is important that agents have behaviors that reflect how individuals actually behave (if known).

  4. It is important that agents adapt and change their behaviors.

  5. It is important that agents learn and engage in dynamic strategic interactions.

  6. It is important that agents have a dynamic relationship with other agents, and agent relationships form, change, and decay.

  7. It is important to model the processes by which agents form organizations, and adaptation and learning are important at the organization level.

  8. It is important that agents have a spatial component to their behaviors and interactions.

  9. The past is no predictor of the future because the processes of growth and change are dynamic.

  10. Scaling-up to arbitrary levels is important in terms of the number of agents, agent interactions and agent states.

  11. Process structural change needs to be an endogenous result of the model, rather than an input to the model.
Note that items 3 and 9 are particularly relevant to the argument for agent-based macroeconomic modeling put forward by Doyne Farmer and Duncan Foley, as discussed in yesterday's post.


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