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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In virtual reality a user encounters a computersimulated environment through the use of a physical interface. The user can interact with the environment to the point of becoming a part of the experience, and the experience becomes reality. Natural and
instinctive body movements are translated by the interface into computer commands. The quest for perfection in this human-computer relationship seems to be the essence of virtual reality technology.
To begin to capture the essence of virtual reality without first-hand experience, it is helpful to understand two important terms: presence and immersion. The sense of presence can be defined as the degree to which the user feels a part of the actual environment. The more reality the experience provides, the more presence it has. Immersion can be defined as the degree of other simulation a virtual reality interface provides for the viewer. A highly immersive system might provide more than just visual stimuli; for example, it may additionally provide simulated sound and motion, and simultaneously prevent distractions from being present.
This study describes a system that has been developed to address a number of these issues. Based on research findings from the field of Artificial Intelligence which expounds on the need for multiple techniques to represent any complex area of knowledge, we have selected a particular approach that focuses on multiple techniques for design representation. We review this approach in depth by considering its many facets necessary when implementing a knowledge-based system. We then partially test the viability of this approach through a small case study, implementing a knowledge-based system for designing stairs. While this effort only deals with a small part of the total design process, it does explore a number of significant issues facing the development of computer-based design assistants, and suggests several techniques for addressing these concerns.
Two approaches to the integration of artificial intelligence and knowledge-based systems into architectural design practice are currently dominant. One attempts to create systems which can on their own produce designs, the other provides intelligent support for those doing design. It was, in part, the recognition of limitations in the ability of traditional CAD systems and building modelers to reflect what designers actually do that led to explorations into the idea of intelligent assistants. Development of such assistants was aided by research into the act and process of design through protocol and other studies. Although some work is currently being done in the development of artificial intelligence and knowledge based applications in architecture, and work continues to be done on the study of design methodologies, the bulk of available information in each of these areas remains in the realm of design disciplines related to but outside of architecture and do not reflect the explicit role of architectural design in the embodiment and expression of culture.
The relationship of intelligence to culture has resulted in some skepticism regarding the ultimate capacity of neural nets and symbolically programmed computers in general. Significant work has been done questioning the rational tradition in computer development for its failure to address phenomena which are not easily subject to scientific analysis. Further skepticism regarding the role of artificial intelligence and knowledge-based or expert systems in architectural design has been emerging recently. Such criticism tends to focus on two issues: the nature of drawing as an activity which involves both the generation and interpretation of graphic artifacts, and the nature of the human designer as an active agent in the design process.
In design search, design evolves from one state to another by exhaustively or heuristically applying proper rules. Each rule application involves, first, pattern-matching the antecedent of a rule to the current state and, second, transforming the matched portion of that state into the consequence of the rule. However pattern-matching techniques of current CAAD systems are still limited. In current CAAD systems, only those two squares can be dealt with by patternmatching for further development. However, a human designer can effortlessly recognize not only those two but other emergent subshapes, for example a smaller square in the middle where the two squares overlap and two L-shapes in the corners. Therefore a human designer can thoroughly deliberate all these alternatives before making a decision. In other words, human designer is capable of restructuring shapes in terms of emergent subshapes in any step of designing.
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