Artificial Intelligence in Design '91J. S. Gero Artificial Intelligence in Design '91 is a collection of 47 papers from the First International Conference on Artificial Intelligence in Design held at Edinburgh in June 1991. The papers in this book are grouped into 13 headings, starting with a background of AI design systems and to which extent AI that results from being used as planning tool be applied to quality-oriented design processes in architecture. A constraint-driven approach to object-oriented design is also shown on real-world objects. The use of CADSYN in the structural design of buildings is examined, along with design-dependent knowledge and design-independent knowledge. Discussions on empowering designers with integrated design environments are given whereby design objects may be retrieved from catalogues without requiring users to form queries. Mention is given to automated adjustment of parameter values frequently used in computer routine applications. The book also introduces the Computer Aided Design (CAD) as applied to architecture. Design representation using data models, non-monotonic reasoning in design, and the cognitive aspects of design using empirical studies are discussed. Topics of the industrial applications of AI in design, such as the needed steps to develop a successful AI-based tool, and a review of the Castlemain Project and telecommunication distribution networks follow. This book is suitable for programmers, computer science students, and architects and engineers who use computers in their line of work. |
From inside the book
Results 1-5 of 76
Page 5
... represented using a state space, where each state corresponds to a possible design. Each of the possible designs can be considered a solution (either intermediate or final), and therefore, we can also refer to it as a solution space or ...
... represented using a state space, where each state corresponds to a possible design. Each of the possible designs can be considered a solution (either intermediate or final), and therefore, we can also refer to it as a solution space or ...
Page 35
... represented by a structural relation graph (Flemming U., 1989) describing the space structure, manipulated by means ... represents the context using an orthogonal graph and a list. The input of the module is given by the geometric ...
... represented by a structural relation graph (Flemming U., 1989) describing the space structure, manipulated by means ... represents the context using an orthogonal graph and a list. The input of the module is given by the geometric ...
Page 66
... represents a different cycle. A larger square means that a unit is fully active and a dot means that the unit is inactive. Eventually the system settles into the stable state represented by the rightmost column. We can observe the ...
... represents a different cycle. A larger square means that a unit is fully active and a dot means that the unit is inactive. Eventually the system settles into the stable state represented by the rightmost column. We can observe the ...
Page 67
... represented loosely as a 'landscape'. When different combinations of units are clamped, the topography of the landscape is modified: peaks are moved and distorted. The range of potential room types is varied as a consequence. Otherwise ...
... represented loosely as a 'landscape'. When different combinations of units are clamped, the topography of the landscape is modified: peaks are moved and distorted. The range of potential room types is varied as a consequence. Otherwise ...
Page 81
... represented graphically as a network. Figure 1 is an example constraint network for hole specification on printed wiring boards. The objective of a SPARK program is to find a set of variable values that doesn't violate any of the ...
... represented graphically as a network. Figure 1 is an example constraint network for hole specification on printed wiring boards. The objective of a SPARK program is to find a set of variable values that doesn't violate any of the ...
Contents
1 | |
Learning in design1 | 247 |
Learning in design2 | 301 |
Nonmonotonic reasoning in design | 421 |
Conceptual design | 643 |
Applications of AI in design | 783 |
Integrated designsystems and tools | 857 |
Author index | 941 |
Author electronic addresses | 942 |
Other editions - View all
Common terms and phrases
abstraction action activity algorithm alternative analysis application approach architecture artifact Artificial Intelligence attributes automated behavior blackboard blackboard system CAAD CAD system case-based reasoning circuit design complex components computer-aided design concept connectionism connectionist constraints construction context database decisions decomposition defined described design knowledge design object design problem design process design solution design system design task design variables design-dependent device domain knowledge domain theory drug design elements evaluation example expert system function geometric Gero goal heuristics hierarchy ICADS identify implemented inference input instance instantiated integrated interaction interface knowledge base knowledge representation knowledge sources knowledge-based learning machine learning mechanism method modified module nodes object-oriented operation optimisation parameters performance pharmacophore Prolog qualitative relationships representation represented rules selection semantic space specific structure sub-system truth maintenance system values