  Current robot architectures for modeling interaction behavior are not well
suited to the dual task of sequencing discrete actions and incorporating
information instantly. Additionally, for communication based on body motion,
actions also serve as cues for negotiating interaction alternatives and to
enable timely interventions. The paper presents a dynamical system based on the
stable heteroclinic channel network, which provides a rich set of parameters to
isntantly modulate motions, while maintaining a compact state graph abstraction
suitable for reasoning, planning and inference.
