Case-based design support: a case study in architectural design ...

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Michael Pearce, Galaxy Scientific Corporation. Ashok K. Goel, Janet 1. Kolodner ..... Michael Pearce, Louise Penberthy, Murali Shan- kar, Robert Simpson, and ...
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A Case Study in Architectural Design Michael Pearce, Galaxy Scientific Corporation Ashok K. Goel, Janet 1. Kolodner, Craig Zimring, Lucas Sentosa, and Richard Billington, Georgia Institute of Technology

facts involves a series of decisions. To design an office building, you might make decisions about applying abstract design concepts and skeletal design plans, selecting specific systems and components, retracting earlier decisions, relaxing design constraints, accepting design solutions, and so on. How hard it is to make these decisions

decisions. For the office building, we might have many possible spatial configurations that do not correspond directly to design constraints, making it hard to select among them. If the architect does not have the appropriate knowledge, poor decisionsand poor designs-can result. Thus, providing good decision support for architects and other designers is a real challenge for researchers on intelligent computer-aided design.

choices. However, despite the apparent abundance and extensive use of past designs in decision making, architects do not always have easy access to appropriate cases. They are not organized in libraries, 14

W E WANTED TO FIND OUT WHETHER A LARGE CASE LIBRARY COULD SUPPORT HUMAN DECISION MAKING IN A COMPLEX TASK SUCH AS DESIGN. WHILE THE ARCHIE SYSTEM MET MANY OF OUR GOALS, WE LEARNED JUST AS MUCH FROM ITS LIMITATIONS.

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but are scattered in file cabinets, magazines, books, and the memories of other designers. Some large architectural firms have small libraries of proprietary designs, but typically they are indexed with just a few mnemonic features that do not always indicate a past design's relevance to a current design problem. To find out whether large case libraries can support and improve human decision making in complex tasks,' we decided to

access to domain experts and experience as naive users of office buildings. (3) The system should support conceptual as opposed to detailed design, because this is generally the more difficult and innovative part of the process, and becausetheseearlydecisions haveamajor impact on what follows. We also decided to support design proposal and critiquing, two subtasks of conceptual design.

(1) The system should support common design tasks but leave all decisions to the user. (2) The system should apply to the design of office buildings, because we had

represent, index, and retrieve architectural design cases, our early work focused on developing a vocabulary for representing and organizing such cases in a library, and on schemes for retrieving those relevant to

OXX5/9000/92/1000-0014$3 00 0 1992 IEEE

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0-Goal Group interaction

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0-Goal Organization type

Figure 1. A design case in Archie.

a given design task. While building and using Archie, we encountered other issues whose importance we did not fully appreciate at first, but that we are now exploring in two parallel projects: Archie2 and Archie Tutor.

lllustrative examples Archie helps architects in the high-level task of conceptual design as opposed to low-level tasks such as drawing and drafting, numerical calculations, and constraint propagation.

design plans that specify building components (such as walls, doors, and furniture) and a satisfactory configuration; outcomes that describe how well the plan satisfies its goals and constraints (explicit and implicit) from a specific point of view (for example, a design outcome could be that auditory privacy was low); and lessons to be learned from the case (not shown), indicating in which situations the case will be useful, provided to the user as text annotations so they are easy to understand. The goals and outcomes prefixed by “0” in the figure pertain to the client organiza-

Proposing a design. Archie gives architects access to office building designs created by other architects, and points to factors that must be considered in solving a given design problem. Each case in Archie contains several types of information (see Figure 1 )?: design goals (such as group interaction) andconstraints (such as a partition height above eye level):

tion and describe the people who use the building and their interactions with that building. The goals, plans, and outcomes prefixed by “C” describe the core, or permanent aspects, of the building. For example, the total area of the design described in Figure I is about 14,500 square feet and is likely to remain the same over time. Features prefixed by “P’specify the building partitions, the nonpermanent interior structures that divide the space. For example,

one changeable aspect ofthe plan in Figure 1 is that the manager’s office has glass walls. Features prefixed by “F’ represent furniture. For example, one outcome of the design in Figure 1 is that the furniture color was pleasing. A session with Archie begins as a client outlines a set of requirements for an office building-let’s say office space for a small accounting firm: Since customers frequently visit the company offices, the image projected by the office space is very important. Given the nature of the work to be done there, the offices need facilities for faceto-face contact and group interaction. The company is dynamic and growing, so the design should allow for future modifications. Since the company maintains paper files on its clients, the offices must have a good filing system. The company needs about 12.000 square feet of space and has budgeted $300,000 for partitions and furniture. The architect uses Archie’s vocabulary to prepare a probe representing the customer’s

similar design problems, and can combine solutions from several cases to create a high-level qualitative design that achieves the client’s goals. For example, the case in Figure 1 uses an open office plan to achieve flexibility, face-to-face contact, and group interaction. An open architectural plan implies low, movable partitions to separate office spaces rather than fixed ceiling-tofloor walls. Since face-to-face contact and employee interaction are important design goals in the current problem, the architect might adopt the open office plan of the previous case. The architect copies features from interesting cases to produce a partially specified conceptual design for the new office building. In this way, Archie helps architects brainstorm by letting them explore previous cases for ideas and inspirations.

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Figure 2. Probing Archie‘s case memory.

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F G e 3. Model of lighting quality.

design goals and constraints (see Figure 2 ) Each box in the figure represents a feature i n the probe The feature’s name is on the left, its balue is on the right, and the label\ to the right ot each box describe the type ot value it can tdke Fedtures in probes use the same “0,”“C,” and “F’prefixes that case features use (see Figure 1 ) Having received a probe, Archie cdlcu~~~~~~

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lates a similarity value for each stored case based on how close each concept value i s to specified values in the probe and on the concept’s importance. It retrieves cases whose similarity value is above a predetermined threshold. Figure 1 is part of a case retrieved by the probe i n Figure 2. Browsing through the retrieved cases, the architect sees how other architects solved

Critiquing a design. With a partially specified conceptual design in hand, the architect can now critique the design to locate potential problems. This mode of operation involves more focused reasoning: The architect wants detailed information within a narrow context. For example, the architect may be concerned with the quality of lighting i n a proposed office design, and selects one of several qualitative domain models in Archie that represent the perspectives of different experts on that aspect of the design (see Figure 3). Figure 4 shows the part of a retrieved case that pertains to lighting, including design goals, plan critiques, lessons learned, and so on. Comments on the case are expressed as text annotations (shown in shaded boxes): Goal comments refer to interactions among design goals, plan comments specify individual design decisions and their relations to goals, outcome comments explain the outcomes, and case comments provide general background on the building’s design. T h e “ 0 - O u t c o m e : Moral” list, enclosed in adouble box. specifies the lessons learned from the case. The “C-Outcome: Lighting SatisfactionArtificial” feature, also enclosed in a double box, shows that the glare problems that led Archie to retrieve this case were caused by artificial lighting. The “0-Outcome: Moral” tells the architect how to modify the proposed design (by using diffusers over bulbs). After fixing this aspect of the design, the architect might similarly critique the

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*Designfor a wide variety of users ‘Information technology Goal comments

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*All offices have fixed partitions, no

modular furniture used except in Plan secretary bays comments ‘Central hallway with offices on both sides (managerson outside) *Hodgepodge of furniture systems

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Outcome comments

*Not much interaction with workers outside workgroup ‘Easy to adjust workgroup size

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igure 4. Case features associated with lighting quality. I

design from other perspectives. This process of retrieving, critiquing, and adapting continues until the architect is satisfied with the design.

System implementation We built Archie using Remind, Cognitive Systems’ case-based knowledgeengineering shell.’ The tool lets programmers design a case representation, enter case information, set up a retrieval mechanism, and design a presentation format. Remind includes a graphical function editor for dynamically computing features, a direct manipulation editor for designing ~. case displays, and a retrieval explanation editor. All the figures i n this article are based on Archie screens that were produced using Remind. Cases in Archie describe specific building designs. We collected about 20 cases from three sources. Some are based on our experiences in the office buildings where we (one or more ofthe authors) have worked. We also used professional architectural journals, whose articles typically deal with

a specific aspect of a building such as aesthetics, furniture systems, lighting systems, and so on. Finally, we used postoccupancy evaluations written by architects and researchers who were trying to identify the sources of a building’s problems and suggest ways (based on cost and effort) to fix them. Thus, the quality and completeness of information in Archie’s cases vary widely.

Knowledge organization. Archie contains three kinds of knowledge: primitive concepts, domain models, and design cases. Primitive concepts refer to the primitive objects, relations, and parameters of office buildings, and form part of the language for representing and indexing cases. Domain models capture the causal relationships among case concepts. Cases in Archie are represented as flat, static frames, each with more than 150 possible features Features can be concepts, text, integers, real numbers, or functions Most features are concepts, with some numbers and text Archie’s features originated from three wurces From our analysis of office build~~

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ings, we developed features that differentiate one building from another, including descriptions of users, rooms, equipment, and users’ likes and dislikes. Other features came from the domain models that describe outcomes. For example, the color of the walls, floor, and furniture all affect the amount of glare in a office, so these features were added to the representation language. Finally, some features developed from usability issues. Understanding a case by reading the concept features in its description can be difficult because of the large number of features. Since users must understand the points a case is trying to make but don’t have to understand Archie’s representation scheme, we added textual features to create a more natural interface. The number of features in Archie grew rapidly as we analyzed the first few cases, but then stabilized after about 10 cases.

Case retrieval. Remind gives Archie two mechanisms for retrieving cases: nearest-neighbor matching and model-based clustering. These mechanisms are used in the brainstorming and focused-problem-

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Figure 5. A partial concept hierarchy.

solving modes of operation, respectively, which we described earlier.

Primitive concepts and nearest-neighbor matching. Archie uses nearest-neighbor matching and primitive concepts to retrieve building designs that satisfy a problem’s goals and constraints. The concept features that form Archie’s representation language are organized hierarchically to specify the goals, plans, and outcomes of design cases. Concept slots are the most important features for case retrieval because they represent classes of objects and their partial orderings. Some of Archie’s concepts pertain to domain objects such as lighting devices; others are more abstract, such as lighting quality. Figure 5 shows a small subset of these concepts. Concept nodes with squares in their boxes have subnodes that can be expanded into the values that the concept can take. For exam-

ple, Archie knows that lighting devices can be fluorescent, halogen, or incandescent. The “