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AI Magazine
Analogical representations of naive physics
Artificial Intelligence
Representations of commonsense knowledge
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ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Automatic depiction of spatial descriptions
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
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Representation and processing of spatial expressions
Representation and processing of spatial expressions
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Qualitative structural analysis using diagrammatic reasoning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Diagrammatic reasoning and cases
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Mental representation and processing of geographic knowledge
Artificial Intelligence Review
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SC'10 Proceedings of the 7th international conference on Spatial cognition
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A common motivation for developing computationalframeworks for diagrammatic reasoning is the hope thatthey might serve as re-configurable tools for studyinghuman problem solving performance. Despite the ongoingdebate as to the precise mechanisms by which diagrams,or any other external representation, are used inhuman problem solving, there is little doubt thatdiagrammatic representations considerably help humanssolve certain classes of problems. In fact, there area host of applications of diagrams and diagrammaticrepresentations in computing, from data presentationto visual programming languages. In contrast to boththe use of diagrams in human problem solving and theubiquitous use of diagrams in the computing industry,the topic of this review is the use of diagrammaticrepresentations in automated problem solving. Wetherefore investigate the common, and often implicit,assumption that if diagrams are so useful for humanproblem solving and are so apparent in humanendeavour, then there must be analogous computationaldevices of similar utility.