Agent-Based Models in the Real World

thought_process1A recently published News Feature in Proceedings of the National Academy of Sciences by Robert Frederick, titled Agents of Influence, discusses the advancing state of agent-based models (ABMs) and their growing use to inform business and policy decisions. Businesses are employing ABMs to find new efficiencies in complex supply chains, and research efforts to create million-agent models of the economy may soon offer insight into the dynamics of our financial systems and broader economy.

What I like most about this article is that it illustrates how ABMs and complexity thinking are beginning to make their way out of academics and into the real world. A recent example is how Southwest Airlines used ABMs to find more efficient cargo shipping routes, saving the airline millions of dollars. ABMs as virtual laboratories are getting attention, too. The article describes how these models enable decision-makers to explore the consequences of particular business or policy decisions though a range of possible scenarios.

The message is clear: representing heterogeneous, distributed decision-making creates more realistic models, and is enabling researchers, businesses, and policy-makers to navigate complex systems like never before.

Importantly, Frederick does not shy away from the limitations of such models. What is gained in realism by using ABMs often comes at the cost of having to make numerous simplifying assumptions about human behavior. After all, an ABM is only as good as its description of human decision-making processes, which are notoriously unpredictable.

A great closing quote: “Ultimately, … none of these [ABMs] will offer iron-clad predictions, because they have to make simplifying assumptions about human behavior. The true test will be whether those assumptions, and the resulting outputs of the models, convince policymakers to act on their advice.”

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