Sociologists often model social processes as interactions among variables.We review an alternative approach that models social life as interactions amongadaptive agents who influence one another in response to the influence theyreceive. These agent-based models (ABMs) show how simple and predictable localinteractions can generate familiar but enigmatic global patterns, such as thediffusion of information, emergence of norms, coordination of conventions, orparticipation in collective action. Emergent social patterns can also appearunexpectedly and then just as dramatically transform or disappear, as happensin revolutions, market crashes, fads, and feeding frenzies. ABMs providetheoretical leverage where the global patterns of interest are more than theaggregation of individual attributes, but at the same time, the emergentpattern cannot be understood without a bottom up dynamical model of themicrofoundations at the relational level. We begin with a brief historicalsketch of the shift from “factors” to “actors” incomputational sociology that shows how agent-based modeling differsfundamentally from earlier sociological uses of computer simulation. We thenreview recent contributions focused on the emergence of social structure andsocial order out of local interaction. Although sociology has lagged behindother social sciences in appreciating this new methodology, a distinctivesociological contribution is evident in the papers we review. First,theoretical interest focuses on dynamic social networks that shape and areshaped by agent interaction. Second, ABMs are used to perform virtualexperiments that test macrosociological theories by manipulating structuralfactors like network topology, social stratification, or spatial mobility. Weconclude our review with a series of recommendations for realizing the richsociological potential of this approach.