Although the mathematical foundations of common value auctions have been well understood since Milgrom & Weber (1982), equilibrium bidding strategies are computationally complex. Very few calculated examples can be found in the literature, and only for highly specialized cases. This paper...

Acceptance of computer modeling and experimentation has spread slowly at best in economics in large part because agent-based models often seem foreign to the neoclassical core of economics, as that core is understood today. But in its beginnings neoclassical economics was not built from choice...

Economic growth depends not only on how people make decisions but also upon how their decisions are coordinated. Because of this, aggregate outcomes can diverge from individual intentions. I illustrate this with reference to the modern literature on economic growth, and also with reference to an...

This chapter treats a variety of epistemological issues surrounding generative explanation in the social sciences, and discusses the role of agent-based computational models in generative social science.

Using the author's own experiences, this chapter shows how agent-based modeling (ABM) can address research questions common to many disciplines, facilitate interdisciplinary collaboration, provide a useful multidisciplinary tool when the math is intractable, and reveal unity across disciplines....

An agent-based model is a virtual world comprising distributed heterogeneous agents who interact over time. In a spatial agent-based model the agents are situated in a spatial environment and are typically assumed to be able to move in various ways across this environment. Some kinds of social...

Social-ecological systems are complex adaptive systems where social and biophysical agents are interacting at multiple temporal and spatial scales. The main challenge for the study of governance of social-ecological systems is improving our understanding of the conditions under which cooperative...