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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures
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1. Brown, G.Z. and Novitski, Barbara-Jo (1988) A Macintosh Design Studio

Computing in Design Education [ACADIA Conference Proceedings] Ann Arbor (Michigan / USA) 28-30 October 1988, pp. 151-162 https://doi.org/10.52842/conf.acadia.1988.151
2. McIntosh, Patricia G. (1988) A Computational Tutor for Architectural Design

Comput., Environ. and Urban Systems USA: 1988. vol. 12: pp. 213-219. includes bibliography. https://papers.cumincad.org/cgi-bin/works/Show?6354
3. Oksala , T. (1988) Logical Models for Rule-based CAAD

CAAD futures ‘87 [Conference Proceedings / ISBN 0-444-42916-6] Eindhoven (The Netherlands), 20-22 May 1987, pp. 107-116 https://papers.cumincad.org/cgi-bin/works/Show?404e
4. Pea, R. (1993) Practices of Distributed Intelligence and Designs for Education

Distributed Cognitions, edited by G. Salomon. New York, NY: CambridgeUniversity Press https://papers.cumincad.org/cgi-bin/works/Show?98bd
5. Pearson, D.G., Alexander, C. and Webster, Robin (2001) Working Memory and Expertise Differences in Design.

J. S. Gero, B. Tversky and T. Purcell (eds), 2001, Visual and Spatial Reasoning in Design, II - Key Centre of Design Computing and Cognition, University of Sydney, Australia https://papers.cumincad.org/cgi-bin/works/Show?7d26
6. Reich, Yoram (1988) Machine Learning for Expert Systems : Motivation and Techniques

i-iii, 51 p. : some ill Pittsburgh, PA: Engineering Design Research Center, CMU, June, 1988. EDRC 12-27-88. includes bibliography. First generation expert systems suffer from two major problems: they are brittle and their development is a long, effortful process. Few successful expert systems for real world problems have been demonstrated. In this paper, learning, the key to intelligent behavior and expertise, is described as the answer to both expert systems deficiencies. Machine learning techniques are described, with their applicability to expert systems. A framework to organize machine learning techniques is provided. The description is followed by examples taken from the structural design domain. AI / learning / expert systems / structures / techniques. 37. Requicha, Aristides A. G. 'Mathematical Models of Rigid Solid Objects -- Production Automation Project.' Rochester, NY: College of Engineering & Applied Science, University of Rochester, November, 1977. [3], 37 p. : ill. https://papers.cumincad.org/cgi-bin/works/Show?252a
7. Schmitt, G. (1988) Expert Systems and Interactive Fractal Generators in Design and Evaluation

CAAD futures ‘87 [Conference Proceedings / ISBN 0-444-42916-6] Eindhoven (The Netherlands), 20-22 May 1987, pp. 91-106 https://papers.cumincad.org/cgi-bin/works/Show?2622
8. Wastell, D.G. and White, P. (1993) Using Process Technology to Support Cooperative work: Prospects and Design Issues

CSCW in Practice: An Introduction and Case Studies. pp. 105-126. Edited by Dan Diaper and Colston Sanger, London: Springer-Veriag https://papers.cumincad.org/cgi-bin/works/Show?0051
9. Yeh, A. G. (1988) Microcomputers in urban planning: applications, constraints and impacts

Environment and Planning B : Planning and Design 15, pp. 241-254 https://papers.cumincad.org/cgi-bin/works/Show?ea75

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