Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-27T07:55:58.417Z Has data issue: false hasContentIssue false

A compositional approach to modelling design rationale

Published online by Cambridge University Press:  27 February 2009

Frances M.T. Brazier
Affiliation:
Artificial Intelligence Group, Department of Mathematics and Computer Science, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands.
Pieter H.G. van Langen
Affiliation:
Artificial Intelligence Group, Department of Mathematics and Computer Science, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands.
Jan Treur
Affiliation:
Artificial Intelligence Group, Department of Mathematics and Computer Science, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands.

Abstract

Design support systems need to be developed on the basis of an understanding of the human design process to be useful during design. The explicit representation of design history and rationale are of particular importance for explanation and reuse. Within the DESIRE framework for compositional modelling, a generic task model of design has been developed that clearly specifies the role of design history and design rationale within the design process. The model provides a structure to distinguish different types of design rationale, according to the functional role they play in the design process. It has been used to structure the modelling process of an example aircraft design task, which illustrates the various instances of design rationale that can be generated.

Type
Articles
Copyright
Copyright © Cambridge University Press 1997

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Akin, Ö. (1978). How do architects design? In Artificial Intelligence and Pattern Recognition in Computer Aided Design, (Latombe, J.-C, Ed.), pp. 65119. North Holland, Amsterdam.Google Scholar
Brazier, F.M.T., Dunin-Keplicz, B.M., Jennings, N.R., & Treur, J. (1995). Formal specification of multi-agent systems: A real world case. Proc. First Int. Conf. Multi-Agent Systems, ICMAS-95, pp. 2532.Google Scholar
Brazier, F.M.T, Dunin-Keplicz, B.M., Jennings, N.R., & Treur, J. (1997). DESIRE: Modelling multi-agent systems in a compositional formal framework. Int. J. Cooperative Inf. Sys. 6(1), 6794.CrossRefGoogle Scholar
Brazier, F.M.T, van Langen, P.H.G., Ruttkay, Z.S., & Treur, J. (1994) On formal specification of design tasks. In Artificial Intelligence in Design '94, (Gero, J.S., & Sudweeks, F., Eds.), pp. 535552. Kluwer Academic Publishers, Dordrecht.Google Scholar
Brazier, F.M.T, van Langen, P.H.G., & Treur, J. (1995). Modelling conflict management in design: an explicit approach. AlEDAM 9(4), 355366.Google Scholar
Brazier, F.M.T, van Langen, P.H.G., & Treur, J. (1996). A logical theory of design. In Advances in Formal Design Methods for CAD. (Gero, J.S., Ed.), pp. 243266. Chapman & Hall, New York.CrossRefGoogle Scholar
Brazier, F.M.T., van Langen, P.H.G., Treur, J., Wijngaards, N.J.E., & Willems, M. (1996). Modelling an elevator design task in DESIRE: The VT example. Int. J. Human-Computer Stud. 44, 469520.CrossRefGoogle Scholar
Brazier, F.M.T, Treur, J., & Wijngaards, N.J.E. (1996 a). The acquisition of a shared task model. In Advances in Knowledge Acquisition; 9th European Knowledge Acquisition Workshop, EKAW'96, (Shadbolt, N., O'Hara, K., & Schreiber, A.Th., Eds.), Lecture Notes in Artificial Intelligence, Vol. 1076, pp. 278289. Springer Verlag, Berlin.Google Scholar
Brazier, F.M.T, Treur, J., & Wijngaards, N.J.E. (1996 b). Interaction with experts: The role of a shared task model. Proc. Europ. Conf. on AI (ECA1 '96), pp. 241245. Wiley and Sons, Chichester.Google Scholar
Brazier, F.M.T., Treur, J., Wijngaards, N.J.E., & Willems, M. (1995). Formal specification of hierarchically (de)composed tasks. Proc. Ninth Banff Knowledge Acquisition for Knowledge-based Systems Workshop (KAW '95), 2, pp. 25/1–25/20. SRDG Publications, Department of Computer Science, University of Calgary, Calgary.Google Scholar
Brazier, F.M.T, Treur, J., Wijngaards, N.J.E., & Willems, M. (1996). Temporal semantics and specification of complex tasks. Proc. of the 10th Banff Knowledge Acquisition for Knowledge-based Systems Workshop (KAW '96), pp. 15/1–15/17. SRDG Publications, Department of Computer Science, University of Calgary, Calgary.Google Scholar
Brown, D.C., & Chandrasekaran, B. (1989). Design problem solving: knowledge structures and control strategies, Research Notes in Artificial Intelligence. Pitman, London.CrossRefGoogle Scholar
Brumsen, H.A., Pannekeet, J.H.M., & Treur, J. (1992). A compositional knowledge-based architecture modelling process aspects of design tasks. Proc. Twelfth Int. Conf. on Artificial Intelligence, Expert Systems and Natural Language (Avignon-92), pp. 283294.Google Scholar
Candy, L., & Edmonds, E. (1994). Artefacts and the designer's process: Implications for computer support to design. Revue sciences el techniques de la conception 3(1), 1131.Google Scholar
Candy, L., Edmonds, E., & Patrick, D. (1994). On providing interactive knowledge support to conceptual design. Technical Report. Loughborough University of Technology.Google Scholar
Chandrasekaran, B. (1990). Design problem solving: A task analysis. AI Magazine, 11(4), 5971.Google Scholar
Chung, P.W.H., & Goodwin, R. (1994). Representing design history. Proc. Artificial Intelligence in Design '94, pp. 735752. Kluwer Academic Publishers, Dordrecht.Google Scholar
Ganeshan, R., Garret, J., & Finger, S. (1994). A framework for representing design intent. Design Studies, 15(1), 5984.CrossRefGoogle Scholar
Geelen, P.A., & Kowalczyk, W. (1992). A knowledge-based system for the routing of international blank payment orders. Proc. Twelfth Int. Conf. on Artificial Intelligence, Expert Systems and Natural Language (Avignon-92), pp. 669677.Google Scholar
Gruber, T, Baudin, C, Boose, J., & Weber, J. (1991). Design rationale capture as knowledge acquisition: Trade-offs in the design of interactive tools. Proc. Eighth Int. Workshop on Machine Learning, pp. 312. Morgan Kaufmann, Chicago.Google Scholar
Gruber, T, & Russel, D.M. (1990). Design knowledge and design rationale: A framework for representation, capture and use. Technical Report KSL 90–45, Stanford Knowledge Systems Laboratory, Stanford University, Stanford, CA.Google Scholar
Klein, M. (1992). DRCS: An integrated system for capture of designs and their rationale. Proc. Artificial Intelligence in Design '92, pp. 393412. Kluwer Academic Publishers, Dordrecht.Google Scholar
McKerlie, D., & McLean, A. (1994). Reasoning with design rationale: Practical experience with design space analysis. Design Studies, 15(2), 214226.CrossRefGoogle Scholar
Mostow, J. (1989). Design by derivational analogy: Issues in the automated replay of design plans. Artif. Intell. 40, 119184.CrossRefGoogle Scholar
Pahl, G., & Beitz, W. (1984). Engineering design. Springer-Verlag, New York.Google Scholar
Petrie, C.J., Cutkosky, M.R., & Park, H. (1994). Design space navigation as a collaborative aid. Proc. Artificial Intelligence in Design '94, pp. 611623. Kluwer Academic Publishers, Dordrecht.Google Scholar
Schön, D.A. (1983). The reflective practitioner: How professionals think in action. Temple Smith, London.Google Scholar
Smithers, T, Corne, D., & Ross, P. (1994). On computing exploration and solving design problems. In Formal Methods for CAD, (Gero, J.S., & Tyugu, E., Eds.), pp. 293313. Elsevier, Amsterdam.Google Scholar