Kulpa, Z. 1994. Diagrammatic representation and reasoning. Machine GRAPHICS & VISION 3(1/2), pp. 77--103.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....different perceptual cues that affect the amount of search effort that is required for problem solving with diagrams (Zhang 1997) 3. EFFECTS OF DIAGRAMMATIC REPRESENTATIONS A diagram is well represented when the representation supports the cognitive processes in reasoning with the diagram (Kulpa 1994). A well represented diagram is effective in presenting information in a way that makes it easy for humans to perceive and reason with (Mackinlay and Genesereth 1985) However, different diagrammatic representations will not necessarily be equally effective (i.e. computationally equivalent) ....

Kulpa, Z. "Diagrammatic Representation and Reasoning," Machine Graphics and Vision (3:1/2), 1994, pp. 77-103.

....of the study and directions for future research. 2. DIAGRAMMATIC KNOWLEDGE REPRESENTATIONS The diagrammatic representation uses diagrams to represent data and knowledge, and diagrammatic reasoning uses inspection and direct manipulation of the diagram as the primary means of inference (Kulpa, 1994). As Simon pointed out . solving a problem simply means representing it so as to make the solution transparent . Simon, 1981) the diagram can be regarded as a means of representing knowledge so as to facilitate problem solving by making the solution transparent. A diagram is said to be ....

Kulpa, Z. (1994). Diagrammatic Representation and Reasoning, Machine Graphics and Vision, vol. 3, nos.

....1987] the expressions correspond, on a one to one basis, to the components of a diagram describing the problem. Each expression contains the information that is stored at one particular locus in the diagram, including information about relations with adjacent loci. Kulpa claims in [Kulpa, 1994] that: The field of diagrammatic data and knowledge representation, and diagrammatic reasoning has recently become one of the most rapidly growing areas of research in artificial intelligence and related fields of computer science and cognitive science. This is not very surprising due to the ....

Kulpa, Z. (1994). Diagrammatic representation and reasoning. Machine GRAPHICS & VISION, 3(1/2):77--103.

.... and pictorial explanations of mental images involved psychologists and philosophers in lasting debates (see e.g. Block 1981) In more recent years we assisted to a renewed interest in pictorial and diagrammatic representations in AI (witnessed for example by Chandrasekaran and Simon 1992; Kulpa 1994; Glasgow et al. 1995) If compared with the debates of the seventies, this revival is characterised by a more ecumenical mood. Researchers do not aim to individuate a clear cut distinction between two classes of representations (propositional vs. pictorial or similar) nor they believe that such ....

Kulpa, Z. 1994. Diagrammatic Representation and Reasoning. Machine Graphics & Vision 3(1/2): 77103.

.... concerning both its psychological and cognitive sources [9, 26] and mathematical foundations [3, 10, 20, 40] Applications in various fields are also devised and investigated, like in qualitative analysis of physical systems [16, 24] visual programming, graphical interfaces, and mathematics [4, 9, 10, 17, 19, 20, 21]. In this paper we will argue that the diagrammatic representation of interval space may become an important addition to the repertoire of tools of interval researchers, in a somewhat similar manner as a complex plane representation facilitated the development of complex analysis [30] As such, it ....

Z. Kulpa, Diagrammatic representation and reasoning, Machine Graphics & Vision 3 (1994) 77-103.

.... Another possibility is to use more extensively additional representation and reasoning tools, especially the so called analogical representations that are able to model more directly the physical reality, avoiding thus the false roots effects intrinsic in descriptive, propositional formalisms ([6, 24], see Section 4 below) 3.4. Order of magnitude reasoning Humans commonly use another qualitative reasoning device, not accounted for in the qualitative simulation technique described above. It consists in the use of available information about relative orders of magnitude of quantities ....

....systems seems therefore essential for their proper functioning. 4. DIAGRAMMATIC REASONING The field of diagrammatic data and knowledge representation and diagrammatic reasoning has recently become one of the most rapidly growing areas of research in artificial intelligence and related fields [24, 32]. Human problem solvers use diagrams constantly to formulate and communicate problems and as, often indispensable, aids to solve them. Thus, it seems obvious that any computer system which aims at modelling human reasoning ability should be able to use diagrams also. Imagine how it would be like ....

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Z. Kulpa. Diagrammatic representation and reasoning. Machine GRAPHICS & VISION, 3: 77--103, 1994.

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Kulpa, Z. 1994. Diagrammatic representation and reasoning. Machine GRAPHICS & VISION 3(1/2), pp. 77--103.

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Z. Kulpa, Diagrammatic representation and reasoning, Machine Graphics & Vision 3(1-2) (1994), 77--103.

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Z. Kulpa, Diagrammatic representation and reasoning, Machine Graphics & Vision 3(1-2) (1994), 77--103.

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Kulpa, Z. Diagrammatic representation and reasoning. Machine Graphics & Vision, 3: 77--103, 1994.

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Kulpa, Z., "Diagrammatic representation and reasoning" Machine Graphics & Vision, 3, 1994.

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Kulpa, Zenon, 1994. Diagrammatic representation and reasoning. Machine Graphics and Vision, Vol. 3, Nos. 1/2, 77-103, 1994.

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