Artificial life (alife) is the bottom-up study of basic phenomena commonly associated with living agents, such as self- replication, evolution, adaptation, self-organization, exploitation, competition, cooperation, and social network formation. Alife complements the traditional biological and social sciences concerned with the analytical, laboratory, and field study of living organisms by attempting to simulate or synthesize these basic phenomena within computers, robots, and other man-made media. One goal is to enhance the understanding of actual and potential life processes. A second goal is to use nature as an inspiration for the development of solution algorithms for difficult optimization problems characterized by high- dimensional search domains, nonlinearities, and/or multiple local optima. This paper presents a brief overview of alife, stressing aspects especially relevant for the study of decentralized market economies. In particular, a recently developed trade network game (TNG) is used to illustrate how the basic alife paradigm might be specialized to economics. This type of research has recently come to be known as agent- based computational economics.