The creation of interactive computer-controlled characters in interactive media is a challenging and multi-faceted task requiring the skills and effort of professionals from many fields. This work addresses authoring the interactive aspect of these characters’ behaviors – how characters act automatically in response to a dynamic user-controlled character. We present PaintBoard, a system that enables users to prototype and test discrete, real-time, interactive movements in a 2D grid environment simply by digitally painting a storyboard. We designed and developed a novel authoring technique for creating behaviors (painting storyboards) and a novel algorithm based on machine-learning, that analyzes a storyboard to create a behavior that works beyond situations provided in the input storyboard. We conducted two exploratory studies that grounded the prototype design, and present the results of a proof-of-concept workshop with game developers. Finally, we performed a comparison of machine learning algorithms’ performance on our storyboard data.