Confronting complexity: Insights from the details of behavior over multiple timescales

Young children tend to generalize novel names for novel solid objects by similarity in shape; a phenomenon dubbed the shape bias. We believe that the critical insights needed to explain the shape bias in particular, and cognitive development more generally, come from Dynamic Systems Theory. We present two examples of recent work focusing on the real-time decision processes that underlie performance in the tasks used to measure the shape bias. We show how this work, and the Dynamic Systems perspective, sheds light on the controversy over the origins and development of the shape bias. In addition, we argue that the Dynamic Systems perspective is the right level for explanations of development because it requires a focus on the details of behavior over multiple timescales.