Interpersonal synchrony is associated with better interpersonal affiliation. No matter how well-affiliated people are, interruptions or transitions in synchrony rebound to occur. One might intuitively expect that transitions in synchrony negatively affect affiliation or liking. Empirical evidence, however, suggests that time periods with interruptions in synchrony may favor affiliation or liking even more than time periods without interruptions in synchrony. This chapter introduces a controlled adaptive network model to explain how persons’ affiliation might benefit from transitions in synchrony over and above mean levels of synchrony. The adaptive network model was evaluated in a series of simulation experiments for two persons with a setup in which a number of scenarios were encountered in different (time) episodes. Our controlled adaptive network model may serve as a foundation for more realistic virtual agents with regard to synchrony transitions and their role in affiliation.