Diagrammatic reasoning: An artificial intelligence perspective

A common motivation for developing computational frameworks for diagrammati c reasoning is the hope that they might serve as re-configurable tools for studying human problem solving performance. Despite the ongoing debate as t o the precise mechanisms by which diagrams, or any other external represent ation, are used in human problem solving, there is little doubt that diagra mmatic representations considerably help humans solve certain classes of pr oblems. In fact, there are a host of applications of diagrams and diagramma tic representations in computing, from data presentation to visual programm ing languages. In contrast to both the use of diagrams in human problem sol ving and the ubiquitous use of diagrams in the computing industry, the topi c of this review is the use of diagrammatic representations in automated pr oblem solving. We therefore investigate the common, and often implicit, ass umption that if diagrams are so useful for human problem solving and are so apparent in human endeavour, then there must be analogous computational de vices of similar utility.