| authors |
Chen, Chen-Cheng |
| year |
1991 |
| title |
Analogical and inductive reasoning in architectural design computation |
| source |
Swiss Federal Institute of Technology, ETH Zurich |
| summary |
Computer-aided architectural design technology is now a crucial tool of modern architecture, from the viewpoint of higher productivity and better products. As technologies advance, the amount of information and knowledge that designers can apply to a project is constantly increasing. This requires development of more advanced knowledge acquisition technology to achieve higher functionality, flexibility, and efficient performance of the knowledge-based design systems in architecture. Human designers do not solve design problems from scratch, they utilize previous problem solving episodes for similar design problems as a basis for developmental decision making. This observation leads to the starting point of this research: First, we can utilize past experience to solve a new problem by detecting the similarities between the past problem and the new problem. Second, we can identify constraints and general rules implied by those similarities and the similar parts of similar situations. That is, by applying analogical and inductive reasoning we can advance the problem solving process. The main objective of this research is to establish the theory that (1) design process can be viewed as a learning process, (2) design innovation involves analogical and inductive reasoning, and (3) learning from a designer's previous design cases is necessary for the development of the next generation in a knowledge-based design system. This thesis draws upon results from several disciplines, including knowledge representation and machine learning in artificial intelligence, and knowledge acquisition in knowledge engineering, to investigate a potential design environment for future developments in computer-aided architectural design. This thesis contains three parts which correspond to the different steps of this research. Part I, discusses three different ways - problem solving, learning and creativity - of generating new thoughts based on old ones. In Part II, the problem statement of the thesis is made and a conceptual model of analogical and inductive reasoning in design is proposed. In Part III, three different methods of building design systems for solving an architectural design problem are compared rule-based, example-based, and case-based. Finally, conclusions are made based on the current implementation of the work, and possible future extensions of this research are described. It reveals new approaches for knowledge acquisition, machine learning, and knowledge-based design systems in architecture. |
| series |
thesis:PhD |
| email |
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| full text |
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| references |
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| last changed |
2003/05/10 05:42 |
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