Robotic agents can self-organize their interaction with the environment by an adaptive "homeokinetic" controller that simultaneously maximizes sensitivity of the behavior and predictability of sensory inputs. Based on previous work with single robots, we study the interaction of two homeokinetic agents. We show that this paradigm also produces quasi-social interactions among artificial agents. The results suggest that homeokinetic learning generates social behavior only in the the context of an actual encounter of the interaction partner while this does not happen for an identical stimulus pattern that is only replayed. This is in agreement with earlier experiments with human subjects.