An architecture for problem solving with diagrams
In problem solving a goal/subgoal is either solved by generating needed information from current information, or further decomposed into additional subgoals. In traditional problem solving, goals, knowledge, and problem states are all modeled as expressions composed of symbolic predicates, and information generation is modeled as rule application based on matching of symbols. In problem solving with diagrams on the other hand, an additional means of generating information is available, viz., by visual perception on diagrams. A subgoal is solved opportunistically by whichever way of generating information is successful. Diagrams are especially effective because certain types of information that is entailed by given information is explicitly available - as emergent objects and emergent relations - for pickup by visual perception. We add to the traditional problem solving architecture a component for representing the diagram as a configuration of diagrammatic objects of three basic types, point, curve and region; a set of perceptual routines that recognize emergent objects and evaluate a set of generic spatial relations between objects; and a set of action routines that create or modify the diagram. We discuss how domain-specific capabilities can be added on top of the generic capabilities of the diagram system. The working of the architecture is illustrated by means of an application scenario.
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Chandrasekaran, B., Kurup, U., Banerjee, B., Josephson, J., & Winkler, R. (2004). An architecture for problem solving with diagrams. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 151-165. https://doi.org/10.1007/978-3-540-25931-2_16