Diagrammatic reasoning for planning and intelligent control

We describe a possible approach to planning starting from an emerging AI subfield. The models we propose are based on diagrammatic representations for reasoning about dynamic aspects of the world. Diagrammatic knowledge representation is an approach to knowledge representation in AI programs, that is suitable for problem solving and reasoning in spatial domains. Our claim is that diagrammatic representations could offer a way to combine AI and control system techniques for intelligent planning and control. The reason is that diagrammatic representations can share the high-level features of AI formalisms, such as explicit representations of objects, events, and situations, but with a finer-grained decomposition of actions and shapes. The dynamic aspects of our models are based on the metaphor of abstract potential fields (APF).