We argue that the social networks and activity-travel patterns of people interact and coevolve over time. Through social interaction, people exchange information about activity-travel choice alternatives and adapt their latent and overt preferences for alternatives to each other. At the same time, social networks are not static: new social links emerge and existing social links may dissolve in time, depending on activity-travel schedules and the attributes of persons. In this paper we propose a theoretical framework to incorporate these dynamics in microsimulations of activity-travel patterns. A core assumption of the proposed theory is that the utility that a person derives from social interaction is a function of dynamic social and information needs, on the one hand, and of similarity between the relevant characteristics of the persons involved, on the other. Furthermore, persons tend to adapt their preferences so as to increase the utility they derive from their social networks. We derive the theory and models from basic principles and discuss results of a first round of simulations conducted to examine the behavior of the model. We argue that the model is consistent with existing theories and findings in social network analysis.