kalay perf based design

Ž .Automation in Construction 8 1999 395–409

Performance-based design

Yehuda E. KalayDepartment of Architecture, UniÕersity of California, Berkeley, CA 94720, USA

Abstract

Even before Louis Sullivan coined the phrase ‘Form Follows Function,’ architectural researchers have sought, to noavail, a causal relationship between these two primary constituents of the building enterprise. This paper attempts to explainwhy this quest has been futile, and proposes a performance-based design paradigm, instead of the prevailing process-basedparadigms. It suggests that the driving force behind any design activity is the desire to achieve a qualitative solution for aparticular combination of form and function in a specific context. Furthermore, it suggests that quality can only bedetermined by a multi-criteria, multi-disciplinary performance eÕaluation, which comprises a weighted sum of severalsatisfactionrbehavior functions. The paper develops a performance-based design methodology and demonstrates itsapplication in an experimental, knowledge-based CAD system. q 1999 Elsevier Science B.V. All rights reserved.

Keywords: Design methods; Design process; Paradigms of design; Design knowledge; Performance evaluation

1. Introduction

The quest for understanding how humans performcomplex cognitive activities, such as architecturaland engineering design has been the raison d’etre ofˆdesign methods research for the past four decades.Behind this quest stands the need to improve thequality of the built environment, as well as the

Žprocesses of its procurement design, construction,.and management . Why, then, after four decades of

diligent research and development, we find thatbuildings are far from perfect in their ability tosatisfy all the physical, social, cultural, and eco-nomic needs of the people who are affected bythem? Why, in fact, the more we know about thebuilt environment, the less satisfied we are with ourcreations?

In their quest to affect such desired improve-ments, design method researchers have sought to

understand how designers do what they do whenthey design. This understanding would lead, it washoped, to the development of methods and tools thatcan help architects and engineers consistently andreliably achieve desired high-quality results. Manyapproaches have been tried, including psychological,philosophical, and engineering research methodsw x1,3,12,18 .

For the most part, this endeavor has been guidedby the Aristotelian notion that design is a processthat seeks a convergence of form and function: aphysical means that can support certain human needsor activities, subject to certain conditions and con-straints. Following Louis Sullivan’s proclamation that

w x‘Form Follows Function’ 27 , most architecturaldesign methods researchers sought a processes-based,causal relationship between form and function. At

Ž .the core of this quest lay three assumptions: 1 thatŽa physical system’s significant geometrical and ma-

0926-5805r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved.Ž .PII: S0926-5805 98 00086-7

( )Y.E. KalayrAutomation in Construction 8 1999 395–409396

. Ž .terial properties have some function, or utility; 2that one form is more suitable to fulfilling that

Ž .function than other, alternative, forms; and 3 thatfinding a causal relationship between form and func-tion will lead to the development of a method, whichcan be applied with some assurance of success inevery case where a form must be produced that willoptimally facilitate and support a given set of func-tional needs.

Over the past four decades, two differentparadigms of design have emerged, representing twofundamentally different approaches to explaining thecausal relationship between form and function. The

w xfirst, attributed to Simon 24 , attempted to explainthe process of design as a unique instance of generalproblem-solÕing. It postulated that the designer start

Žwith the sought function i.e., the desired behavior.of the system , which is often represented as a set of

goals and constraints. The designer then attempt todiscover a form that will support the desired func-tion, using deductiÕe search strategies.

The other paradigm, called puzzle-making, hasemerged from the work of researchers like Alexan-

w x w xder 4 and Archea 6 . It postulated that designersŽbegin with a kit of forms that include materials as

.well as shape , which are modified and adaptedaccording to certain rules until they achieve somedesired functional qualities. This paradigm is basedon inductiÕe reasoning, and has been modeled with

Žthe aid of analogical inferencing methods meta-.phors, symbols, and case studies .

While logically consistent and computationallyconvenient, neither of these two paradigms, nor theirmany derivatives and permutations, has gained muchfavor with architects themselves. When presentedwith these theoretical paradigms, or better yet—whenexamined ethnographically under actual conditionsw x13 , most architects would not agree that their owndesign process resemble either one of the two

w xparadigms 22 . They would argue that design, espe-cially architectural design, is a serendipitous,‘wicked’ process, replete with uncertainty and dis-

Ž . w xcovery often referred to as the intuitiÕe leap 21 .Instead of the well-behaved theoretical process,which begins with a statement of forms or functions,architectural design often begins with an incubation,introspective phase, followed by iterative refinementof both form and function until some harmonious

w xcoexistence emerges 1 . Thus, while some formsand functions do exist at the outset of the designprocess, neither can be considered the basis forseeking the other. Moreover, the existence of intu-itive leaps introduces discontinuity in the causality-based search process, destroying any hope of devel-oping a coherent method that is based on anymonotonous theory.

If the prevailing paradigms cannot explain howarchitects work, then how can they form a basis forthe development of design tools that purport to assistthem? Indeed, practice has shown that current design

Žtools which are predominantly based on one of the.two paradigms force architects into a methodologi-

cal ‘straight jacket’ which they use only when forcedŽto witness, for instance, the limited success of pre-

.fabricated building systems .This paper proposes an alternative approach to the

understanding of the process of architectural design.It suggests that the quest for design tools must beginnot by exploring how architects design, but rather byasking what they do when they design. An accountof what architects do would stand a better chance tobe accepted by architects, because it will not purportto describe how each individual pursues the designprocess. On the other hand, this changed researchagenda raises the question: how will such an accounthelp bring about the sought improvement in thedesign process or its products? The answer lies inperformance eÕaluation.

The notion of performance is derived from theargument that the relationship between form andfunction is context-based, rather than causality-based. That is, the performance of a proposed designsolution can only be determined by an interpretive,judgmental evaluation, which considers the formŽ .and other physical attributes of the proposed solu-

Ž .tion, the functional objectives goals it attempts toachieve, and the circumstances under which the twocome together. Hence, performance-based designrecognizes that different forms can successfullyachieve similar functions, and that different functionscan often be afforded by similar forms. In addition, itaccounts for performance variances of the sameformrfunction combinations within different con-texts.

The viability of the proposed paradigm, from apractical implementation point of view, depends on

( )Y.E. KalayrAutomation in Construction 8 1999 395–409 397

our ability to represent explicitly, then reason about,the desirability of a particular combination ofform–function-context. Such representation differsfrom common evaluation and simulation procedures,in that it must account for judgment, preferences, aswell as trade-offs and other subjective measures ofsatisfaction.

In the following, we develop the argument forperformance-based design, then, introduce a specificrepresentation of performance. An experimentalframework that implements both the paradigm andthe performance representation measures serves toillustrate the theoretical concepts. Initially, we willuse the terms ‘form,’ ‘function,’ ‘context,’ and ‘per-formance’ loosely, relying on the reader’s intuitiveunderstanding of their meaning. We will define theseterms more precisely in the second part of the paper,where such rigor is needed.

2. Causality-based design paradigms

The notion that Form follows Function is derivedfrom the assumption that a system’s significant geo-

Ž . 1metrical and material properties have some func-tional utility, and that one form is more suitable forfulfilling that function than other, alternative forms.

ŽThis notion and its inverse function is derived from.form , has guided architects and engineers for mil-

lennia. Among its other achievements, this notionhas provided a convenient causal relationship be-tween form and function, the two pillars of architec-tural design, hence, for developing theories andmethods intended to assist architects in performingtheir increasingly more demanding task of findingthe ‘right’ form–function combination.

Many formal theories that were forwarded overthe years to explain what architects do have beenbased on this logical foundation. They can be classi-

w x Ž .fied into two general groups 2 : 1 those that followw x Ž .Simon’s 24 Problem-solÕing paradigm, and 2

w xthose that follow what Archea 6 called Puzzle-mak-ing.

1 In the following, the term FORM will be used to refer to allthe physical attributes of objects, including their material composi-tion, surface finish, etc.

2.1. Problem-solÕing

Problem-solving is a general theory that attemptsto explain the cognitive process of creative thinking.It was first formalized by Simon, Newell and Shawin the late 1950s, and implemented in a computer

Ž .program called GPS General Problem Solver . Prob-lem-solving assumes that the desired effects of someintellectual effort can be stated in the form of con-straints and goals at the outset of the quest for asolution to achieve them. To find the solution, theproblem solver uses a variety of search strategies togenerate successive candidate solutions and test themagainst the stated goals, until one is found that meetsthem. The goals, thus, ‘guide’ the search for asolution right from the beginning of the problem-solving process. Problem-solving assumes that set-

Žting goals i.e., knowing what should be accom-.plished can be separated from the process of finding

a solution that meets them, and that such knowledgecan be acquired through an independent inquiryŽ .analysis , which should be completed before the

w xsearch for a solution has been initiated 1 . Forexample, using this approach, selecting a structuralsystem to span some opening will generally followafter an analysis of forces, cost, and other character-istics of the structure have been determined.

Since the characteristics of the problem, accord-ing to the problem-solving paradigm, are knownprior to commencing the search for the solutionitself, its proponents hold that the search for a‘satisficing’ 2 solution is goal-directed, and there-fore, that means–ends analysis can be employed toguide the search towards finding the desired solution.Thus, the skills that are employed when followingthe problem-solving paradigm are mainly analytical:the ability to compare the current ‘state’ of the

Ždesigned artifact to its desired ‘state’ in terms of its.expected utility and behavior , and the ability to

draw operational conclusions from this comparison,so that the differences can be reduced.

Such goal-driven approaches have been computa-tionally represented as deductive, backward-rea-soning search strategies, where operators are applied

2 Meaning ‘good enough.’ The term was coined by HerbertSimon in his book Sciences of the Artificial, MIT Press, 1969, pp.35–36.


to the goal statement in order to convert it into a setof sub-goals that are easier to solve. This method isapplied recursively until a set of sub-goals that can

w xbe solved without further reduction is found 19 .Examples of tools based on this paradigm include

w xspace allocation programs 7,25 , and a large numberof evaluation programs, such as way-finding and

w xenergy 15,26 .

2.2. Puzzle-making

The assumption that, in architecture, the charac-teristics of the desired solution can be formulatedprior to and independently of the search for thesolution that satisfies them was rejected by critics

w x w xlike Archea 6 and Bijl 8 . They argued that suchknowledge cannot exist prior to the search itself,since the sought solution is unique, and the processof finding it is characterized by discoÕery and has to

w xcontend with uncertainty. Kim 17 and others haveargued that the brief architects are given by theirclients, which often constitutes the basis for thedesign goals, is much too vague, in most cases, toform a complete goal statement. Rather than use theclient’s definition of the desired effects of the soughtbuilding as a complete problem definition, architectscan only use them as a starting point and a catalystfor the design process, something that provides asense of direction and a sounding board for potentialresolutions. They suggest, instead, that architectsmust gradually develop the statement of goals asthey proceed with the design process itself. Theadditional information needed to complete the goalstatement must either be inÕented as part of thesearch process, or adapted from generalized prece-dents, prototypes, and other relevant past experiencesŽ .so-called ‘design cases’ . Since the relationship be-tween the newly invented information, as well as theprecedents, to the particular needs of the problemcan be discovered only as the problem becomesclearer, the adaptation itself is problem-specific andcannot be accomplished prior to engaging in thesearch process itself.

Design, according to this view, is a process ofdiscoÕery, which generates new insights into theproblem. The design search process may, therefore,be compared to puzzle-making—the search for themost appropriate effects that can be attained in uniquespatio-temporal situations through the manipulation

of a given set of components, following a given setof combinatorial rules. Since architects cannot in-vent information from scratch in every case, theyrely on design ‘cases,’ either from the architect’sown experience or from the experience of the profes-sion at large, to provide them with a rich pool ofempirically validated information which has beenrefined through many years of practice and hasgained society’s or the profession’s approval. Thisinformation comes in the form of proven solutionsw x4 , architectural styles, celebrated buildings, estab-lished metaphorical relationships, and recognized

w xsymbolisms 29 . How architects adapt this body ofknowledge to the particular problem at hand is notknown—it is the essence of architecture’s celebrated‘intuitive leap’ and creativity.

Therefore, rather than rely on a goal-driven strat-egy, the puzzle-making paradigm relies on adapta-tion of precedents, symbols, and metaphors. Themain skills employed when following this paradigmare synthetic: the ability to compose given parts intoa new, unique, whole. Such data-driÕen approacheshave been computationally represented as forward-reasoning search strategies: operators are applied tothe current state of the problem with the aim oftransforming it according to pre-set rules. Exampleof tools based on this approach include generativeexpert systems, shape grammars, and case-base de-

w xsign systems 10,14,20 .

3. Other kinds of relationships between form andfunction

In this paper, we argue that the relationship be-tween Form and Function is much more complicatedthan implied by the causality-based notion of ‘FormFollows Function,’ and its inverse. Indeed, a particu-lar form often affords many different functions, anda similar function is often afforded by many differ-ent forms. The following examples will serve toillustrate this argument.

3.1. Many forms, same function

The over-simplicity of the notion ‘Form FollowsFunction’ is evidenced by the multitude of different


forms that essentially were designed to support simi-lar functions. Chairs provide one of the best exam-ples of different forms that were developed to sup-

Ž .port exactly the same function sitting . Design com-petitions, where competitors must respond to thesame set of functional requirements within the samecontext, provide additional evidence that in architec-ture, form does not necessarily follow function. Eachand every competitor will, invariably, produce a verydifferent form for exactly the same function.

Some scholars have tried to explain this apparentlack of causality by arguing that, typically, the func-tional requirements of a building do not tightly con-strain its form, thus, leaving the architect with muchroom to entertain ‘styles’ and other ‘nonpractical’considerations. Herbert Simon, for example, has de-fined style as ‘one way of doing things,’ chosen

w xfrom a number of alternative ways 23 . Since designproblems generally do not have unique or optimalsolutions, says Simon, style can be used to select asolution from among several functionally equiÕalentalternatives, just as any other criteria can. He offersthe following analogy:

‘‘Mushrooms can be found in many places in theforest, and the time it takes us to fill a sack withthem may not depend much on the direction wewonder. We may feel free, then, to exercise somechoice of path, and even to introduce additionalchoice criteria . . . over and above the pragmatic one

Ž .of bringing back a full sack of mushrooms ’’.Most architects, however, would reject this notion

that form is the result of less ‘practical’ functionalconsiderations than other aspects of the building, andtherefore, an afterthought, something to be contem-plated only when all the other ‘important’ aspects ofthe design have been dealt with. Rather, they wouldargue, that it is something a competent architect willconsider before, during, and after the developmentof solutions satisfying the functional needs. More-over, the two issues cannot be separated, since eachone informs the other, and influences its develop-ment.

3.2. Many functions, same form

The notion that a given form can support manydifferent functions is demonstrated well by designsof playgrounds, parks, and civic plazas. Joost van

w xAndel 5 observed that playgrounds for childrenbetween the ages three and seven perform best if theactivities they afford are less structured, in terms ofthe equipment they contain. For instance, placing an

Ž .old fire engine in a playground a form will directthe children’s activities towards particular play pat-terns. Furthermore, van Andel observed that thisparticular form tends to create gender-biased playpatterns, which appeal more to boys than to girls. Onthe other hand, a playground that consists mostly ofa sandbox, some rocks, and a few trees or bushesaffords less restricted play patterns, and is equallyaccessible to both boys and girls. He attributes thisperformance to the creative imagination of the chil-dren, who can adapt the existing, generic forms intoparticular needs, such playing games like ‘house,’‘cops and robbers,’ or the landing of an alien space-ship.

Another example of architectural multi-purposeŽ .i.e., functional spaces has been described by Eliza-beth Cromley in her paper on the history and evolu-

w xtion of modern bedrooms 11 . In addition to provid-ing a place for sleeping, bedrooms, through theseventeenth century, also functioned as parlors, din-ing rooms, and as places for entertaining guests. Inthe eighteenth century, the function of bedroomsbecame more focused, as a place for sleeping anddressing, for quiet retirement, and for socializingwith close friends and family members. In the nine-teenth century, bedrooms became a place to occupyonly at night. In the 20th century, the definition oftheir function was broadened again, especially as faras children’s bedrooms are concerned. Today, suchfunctions include sleeping, doing homework, read-ing, and playing with friends. Bedrooms for the

Ž .adults the so-called ‘Master Bedroom’ , have turnedinto ‘suites,’ which include full bathrooms, dressingrooms, and walk-in closets. They often serve ashome-offices, gyms, and entertainment centers.

The ability of the same form to afford differentfunctions is further demonstrated by what we nowcall adaptiÕe re-use. The term designates the conver-sion of older buildings to meet modern needs. It isrooted in the economic realities of the late 20thcentury, and the growing need for urban renewal andrehabilitation. This trend is characterized by corpora-tions, shops, and even residential units moving intoolder buildings in the core of cities. Rather than tear


down a building which may have some historical orcultural significance, new tenants may rehabilitate itwhile preserving its character. A typical case in pointis Hayes Hall, in Buffalo, NY. Built circa 1865, thislandmark building served as a poorhouse and alunatic asylum until 1893, when it became a countyhospital. In 1909, it was acquired by the Universityof Buffalo, and served as the office of the presidentuntil the new campus was built in 1968, when itbecame the School of Architecture and Planning ofthe State University of New York at Buffalo.

3.3. Other kinds of form–function relationships

Peter Eisneman’s structuralist approach to build-ings, which derives from his own interpretation of

ŽNoam Chomsky’s linguistic theories as well as.Jacques Derrida and other philosophers , demon-

strates well the complexity of the relationships be-tween form and function, as depicted in his design ofHouse X, which is based on a series of geometricaltransformations on a cube.

3.4. The importance of context

The form of a building also depends upon thephysical, cultural, social, and other contexts in whichit is embedded, at least as much as it depends on thefunction it must serve. The form of the Sydney operahouse is an example of a form derived from the

Ž .physical context of the building the Sydney harbor ,Ž .as much as from its function a symphony hall .

Likewise, the shape of Le Corbusier’s RonchampChapel has been derived from its spiritual context, asmuch as from its functional and physical site consid-erations; and Gerrit Rietveld’s colorful Schroder¨

Ž .House in Utrecht, The Netherlands 1931 , has beenshaped as much by the neoclassicist cultural ideas ofthe De Stijl movement to which he belonged, to-gether with painters like Theo van Doesburg and PietMondrian, as much as by functional requirements.

4. Performance-based design

The position taken in this paper is that Form,Function and Context combine to determine the

Ž .behaÕior of the proposed solution Fig. 1 . By ob-

Fig. 1. Performance, as a measure of the confluence of Form,Function and Context.

serving, measuring, and interpreting this behavior,we can assess the performance of the solution.Performance evaluation is intended, therefore, to as-sess the desirability of the behavior of the confluenceof the form, function and context. It may reveal, forexample, that a particular form is capable of support-ing a certain functional need in a particular context,in which case, it will be deemed ‘successful.’ On theother hand, it may reveal a need to modify the formto meet the desired function in the particular context,or to modify the desired function to meet the onesafforded by that form in that particular context.

Designing, accordingly, can be considered as aniterative process of exploration, where desired func-tional traits are defined, forms are proposed, and aprocess of evaluation is used to determine the desir-ability of the confluence of forms and functions

Ž .within the given context Fig. 2 . The process termi-nates when the designer finds a form that fulfills thefunction, or is satisfied by the functionalities af-forded by the chosen form, within the given context.We call this condition functional adequacy: theinstance when form and function come together toachieve acceptable performance within a given con-

w xtext 9 .

4.1. The notion of performance

We suggest that this description of design leads toa different paradigm than either problem-solving orpuzzle-making. We call it performance-based de-sign. As stated earlier, we consider performance tobe a measure of the desirability of the confluence


Fig. 2. Design as a bi-directional exploration of a Form–Function-Context composition.

Žform and function within a given context which, in.turn, we call ‘behaÕior’ . ‘Desirability,’ however, is

a fuzzy and subjective measure. To deal with thisfuzziness, we offer the concept of satisfaction func-tions. Satisfaction curves were first introduced byKunz and Rittel in the 1970s, and used by Mahdavi

Žin his SEMPER programme Automation in Con-Ž . .struction 6 2 : 353–373 . These are mappings that

express the specific relationship between the behav-ior of a system and the subjective measure of itsdesirability under specific circumstances. Fig. 3 de-picts several typical satisfaction curves: on one axis,

they measure the behavior of some aspects of thedesigned system, such as cost, or noise level. On theother, they measure the degree of satisfaction eachbehavior value elicits in the client. Each point onevery curve denotes the performance of the form–function-context combination with regard to some

Ž .measure e.g., cost .The curves demonstrate several phenomena com-

monly associated with satisfaction. Fig. 3b, for ex-ample, demonstrates that the client may generally besatisfied with the behavior of the system, until itsbehavior in some area reaches a certain threshold.

Fig. 3. Some typical satisfaction curves.


Then, satisfaction diminishes, but the change fromŽ . Ž .100% completely satisfied to 0% not satisfied , is

gradual. The curves allow for such notions as ‘quitesatisfied,’ ‘more or less satisfied,’ or ‘barely satis-fied,’ to be expressed. The slopes of the curves allowus to express the rate of change: the steeper theslope, the more abrupt the change, which means thatonce the threshold has been reached, a small changein the system’s behavior will result in satisfaction ordissatisfaction. On the other hand, a shallow slopeindicates a wider latitude in satisfying the client,which allows more room for trade-offs with othersatisfaction curves that may need to be modified.

The satisfaction curves must, of course, be set bythe client, or by the designer. They are unary func-tions, in the sense that each curve pertains to satis-faction derived from one behavior only. This makesit possible to set them individually. For example, theclient may state that his budget for building a singlefamily house is US$300,000. Using the satisfactioncurve depicted in Fig. 3c, he may develop a functionof the kind shown in Fig. 4. It shows that the clientwill be most satisfied if the building costsUS$300,000. He will not be satisfied at all if thebuilding costs over US$315,000, or less thanUS$270,000. The curve also shows that in the vicin-ity of US$300,000, say "US$3,000, his satisfactionis virtually unchanged. The different slopes of therising and diminishing parts of the curve show thatthere is more latitude in satisfying the client’s bud-getary needs under US$300,000 than there is overUS$300,000.

Similar satisfaction functions can be developedfor each aspect of the building. The mappings they

Fig. 4. A satisfaction curve expressing building cost behavior.

afford are expressed as numerical values, each ofwhich expresses the client’s satisfaction with respectto one specific behavior. To aggregate the separatesatisfaction curves into one composite measure ofperformance, we can add them up. But since differ-ent behaviors weigh differently in the overall perfor-mance measure, we must first assign to each of thema relative weight. This method is well-established,and has been used by other researchers to develop

w xaggregates of multi-criteria evaluations 30 . Thecomposite result of the summation of weighted, nor-malized satisfactions is presented to the client as theoverall performance of a given design solution.

4.2. Trade-offs

Trade-offs are the hallmark of every design activ-ity. Typically, all the functional needs of a buildingcannot be satisfied by any one design solution. Theachievement of certain needs often must come at theexpense of other needs. For instance, eliminatingwindows on the west side of a building to saveenergy might also deprive the inhabitants of a fabu-lous view. Hence, the degree of satisfying someneeds may have to be compromised, so that othersare also satisfied. But how much should any oneneed to be compromised? The satisfaction functionsalso facilitate this often difficult decision-makingprocess, in three ways:1. by explicitly showing how well any one need is

being satisfied, as a percentage between full andzero satisfaction;

2. by expressing the tolerance for satisfying theexpressed need, in terms of the steepness of thecurve; and

3. by prioritizing the relative importance of eachneed, in terms of the weight assigned to it.Using these three measures, it is possible to iden-

tify needs that are not being satisfied, and those thatare over-satisfied. It is possible, therefore, to seek adesign solution that better achieves the under-satis-fied needs, while achieving less-well the over-satis-fied needs. In fact, an algorithm can be developedthat provides hints to the designer, indicating possi-ble trade-offs. It first identifies the under-satisfiedneeds, then the over-satisfied ones. Among theover-satisfied needs, it would suggest that those of


Fig. 5. The general multidisciplinary, collaborative design environment.

Žlower importance as expressed by their associated.weights would be candidates for reduced-satisfac-

tion. It will also indicate how much latitude exists inreducing their satisfaction levels.

Given that the inter-relationships between the dif-ferent needs are not obvious, for the most part, the

algorithm cannot tell which specific need ought to becompromised to achieve another need. Such advisecould be added through a knowledge base, whichstores rules about the relationships between the vari-ous needs. It might also store specific suggestions forimproving under-satisfied needs. Nonetheless, only a

Ž .Fig. 6. The structure of an Intelligent Design Assistant IDeA .


complete new design solution can, in general, makeall the necessary adjustments.

5. A case study

To test the validity of the proposed paradigm, wehave implemented it in a test program that operatesin the domain of windows. The program, called TheFenestration IDeA, is a design agent capable of three

Ž . Ž .actions: 1 it provides a simple environment forŽ .developing a set of functional requirements needs

and design solutions that attempt to meet the statedŽ .needs; 2 it evaluates the performance of proposed

Ž .solutions in terms of fenestration only , using fiveŽcriteria daylighting, sound transmission, ventilation,

. Ž .views, and budget ; and 3 it provides advise for

making design changes to achieve the sought degreeof satisfaction, in case it has identified under-satis-fied needs.

The Fenestration IDeA has been developed byGustavo Llavaneras, as part of a larger researchproject, which aims to develop a multidisciplinary,

w xcollaborative design environment 16 . This environ-ment comprises several components, including a

Ž .Project Database PDB for storing the evolving,project-specific design information, and several Ob-

Ž .jects Database ODBs that store object-specific, butŽ .project-independent data Fig. 5 . Intelligent Design

Ž .Assistants IDeAs are the means used to interactwith these databases, while using their expertise indifferent fields to actively assist the designers. TheIDeAs may also call upon external evaluation tools,and may be composed of other, more specialized

Fig. 7. Setting desired satisfaction levels.


IDeAs. Each IDeA is a goal-based agent, comprisingan ActionrDecision system which stores its task-specific rules, a task-specific database, and a group

Ž .of performance predictors and evaluators Fig. 6 .The Fenestration IDeA implements the proposed

paradigm, in a simplified manner. It represents ex-plicitly function and form, as well as the context ofthe particular design project. Function is limited tothe five criteria listed earlier. The designer can setthe desired satisfaction levels for each function, us-

Ž .ing sliders Fig. 7 . The IDeA verifies that thesatisfaction levels set by the designer are withinacceptable building code limits, if such codes existŽ .e.g., for daylighting and ventilation . ‘Acceptablelimits’ are, in turn, dependent upon the overall func-tion of the design: they differ for classrooms, offices,

and private residences, as well as on the locality inwhich they are being built. Hence, the IDeA firstasks the designer to choose the domain of his workŽ .schools, office buildings, residences, etc. , and thelocation of the project. These inputs are used toselect the pertinent knowledge bases, and represent,in their own right, the context of the project.

Once the Context and the Function have beenspecified, the Fenestration IDeA provides the de-signer with the means to design a room with its

Ž .windows Fig. 8 . Again, assistance is provided interms of verifying code compliance for minimal

Ždimensions, as well as other aspects e.g., if thedesigner has indicated that a wall is not an externalwall, the IDeA will not let him put a window in that

.wall .

Fig. 8. Designing the room and its windows.


Fig. 9. Linear piece-wise approximated noise-reduction satisfaction function.

Once the Form has, thus, been specified, theFenestration IDeA performs the necessary tests topredict the behavior of the form–function-contextcombination, and assess its performance. For thesake of simplicity, the Fenestration IDeA approxi-mates the satisfaction curves in a piece-wise linearform. For instance, the noise reduction satisfactioncurve is approximated using the functions depictedin Fig. 9, as expressed by the following equations:

0 if x-MinL° ¶y1 if MinLFxFDesL~ •f x s ,Ž .y2 if DesL-xFMaxL¢ ß0 if x)MaxL

with

MLS MinLyDesL yMinL MLSy100Ž . Ž .y1s ž /MinLyDesLŽ .

MLSy100q xž /MinLyDesL

and

y2

MLS DesLyMaxL yDesL 100yMLSŽ . Ž .s ž /DesLyMaxLŽ .

100yMLSŽ .q x .ž /DesLyMaxL

The overall performance is calculated and pre-sented in numerical and visual forms, as depicted inFig. 10.

The Fenestration IDeA has not yet progressed tothe advise-giving level. It is envisioned, however,that such advise will be provided using the methodoutlined earlier: the system will identify the least-satisfied functions, and the ones that are well-satis-fied yet have some latitude in lowering their level ofsatisfaction. Then, using the task-specific knowl-edge-bases available to it, the system could identifystrategies for satisfying the under-satisfied functions.For example, if the noise-reduction function is notsatisfied, but there is some room for reducing thesatisfaction of the budget requirement, the Fenestra-tion IDeA may suggest using a more expensive


Fig. 10. Several different ways for presenting the overall performance.


triple-glazed window, instead of the selected two-pane window. Likewise, if the noise reduction func-tion is satisfied, but the budget has been exceeded, itwould recommend trying a cheaper two-pane glazinginstead of the selected three-pane.

6. Conclusion

The development of computational tools that cantruly assist humans in performing complex activitiessuch as architectural design relies upon developing adeep understanding of the process that is to beassisted, and on casting this understanding into a

Žmodel that can be represented explicitly and thus.can be translated into a computer program . Having

identified the two main characteristics of architectureas Form and Function, the search for formal theoriesthat can explain the process of design tended toconverge on causality-based paradigms. Hence, theattractivity of statements such as ‘Form followsFunction.’ This statement provided a convenient log-ical foundation for design theories, much like othercausalities have formed the foundation of many engi-neering and practically all scientific paradigms.

Many architects found this logically-convenientstatement inadequate to describe what their experi-ences taught them, for it failed to account for thediscontinuity in the relationship between form andfunction, which architects call ‘the intuitive leap.’This leap occurs when architects, engaged in thesearch for a form that will facilitate some desiredfunction, actually find the ‘right’ form. The paradigmpresented in this paper attempts to recognize thisexperience, and use it as a basis for an alternativeformal model of design, which can be implementedby computational means. It does not attempt toformalize the intuitive leap itself, only to accommo-date it in the model. This accommodation takes theform of contextuality: the convergence of form andfunction in a particular context. The paradigm strivesto eliminate the precedence of either form or func-tion and, hence, of the causal relationship betweenthe two. To compensate, it develops the notion ofperformance, as a means for interpreting and deter-mining the confluence of the two entities.

Performance is a measure of the desirability of thepredicted behavior of a design solution. To facilitate

the computation of performance, satisfaction func-tions were introduced. These functions allow formapping a given behavior onto measures of satisfac-tion. They also facilitate trade-offs, a necessarymeans to improve the overall performance of a sys-tem by sacrificing the degree of satisfaction fromsome parts of the system in favor of others.

The proposed design paradigm fits well withinour view that computers ought to be partners in thedesign process, tools the designer can draw uponwhen developing forms, specifying functions, and

w xinterpreting their confluence 28 . This approach,along with the proposed paradigm, have been testedthrough the development of an experimental systemintended to support the design of windows in abuilding. The so-called Fenestration IDeA has beenimplemented in Visual Basic 4.0. While it is not yetcomplete, we believe it already demonstrates wellthe issues underlying the Performance-based designparadigm.

Acknowledgements

The author wishes to thank Gustavo Llavaneras, aPhD student in the Department of Architecture at UCBerkeley, whose dissertation work helped developedthe paradigm, and who has been implementing itthrough the Fenestration IDeA that was presented inthe paper. Thanks are also due to Professor CarloSequin from the Department of Computer Science at´Berkeley, for his insight and assistance in developingthe Satisfaction Curves.

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