summaries 5 key papers ms bittermann

8/12/2019 Summaries 5 Key Papers MS Bittermann

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List of five selected key publications by Michael S. Bittermann

The publications can be obtained from this website: http://bk.tudelft.nl/cid

1. Bittermann, M.S., Ciftcioglu, Ö.: A cognitive system based on fuzzy information processing and multi-

objective evolutionary algorithm. In: Proc. IEEE Congress on Evolutionary Computation - CEC 2009, IEEE,

Trondheim, Norway (2009) 1271-1280

A cognitive system is described that is capable of finding solutions that satisfy multiple, soft objectives. That

is, objectives are characterized by imprecision or uncertainty, such as ‘high visual privacy.’ The system is

unique in particular with respect to its ability to deal with softness of objectives stemming from the general

complexity of design problems. This is a relevant contribution, as it uniquely emulates the human-like

reasoning and exploration activities associated with handling of complex problems. The publication is

relevant to my academic profile, as it manifests my capability of integrating different advanced

computational methods to address generic complexity issues; in particular this refers to neural, fuzzy and

evolutionary computation being synthesized. My own personal contribution is to the conceptual design of the

system, i.e. the determination of the role of each component, with an associated computer algorithm, namely

genetic algorithm. This way, the system mimics human-like creative activity, namely employing fuzzyinformation processing to estimate satisfaction of objectives, while evolutionary algorithm takes care of the

exploratory aspect of the intelligent design activity. I also verified the validity of the approach by means of

application.

It is emphasized that the importance of this work is that it demystifies design to some extent, which is

generally considered a formidable endeavor. This challenge has remained unresolved until very recently,

notably also since the introduction of computers, and it is partly resolved by this paper. The first cause for the

toughness of the challenge is the extraordinary complexity of design, being a phenomenon involving brain

processes and mind, which are both phenomena that are poorly understood to date. The second cause has

been the lack of adequate computing methodologies that are able to handle the complexity. The publication

uniquely identifies that design is at its essence a search for multi-objectivity with soft objectives, and it

provides an adequate approach to deal with it. This may be an important contribution with respect to

understanding of design and enhanced effectiveness of executions in the profession of architecture, which is

subject to direct support by scientific means through the method presented in the paper.

2. Bittermann, M.S., Sariyildiz, I.S., Ciftcioglu, Ö.: Visual perception in design and robotics. Integrated

Computer-Aided Engineering 14 (2007) 73-91

A mathematical model of visual perception is introduced, where perception is treated as a probabilistic

process. This is a significant accomplishment, as human vision is a complex process due to the underlying

brain processes, so that it has not been modeled with precision before, although this is desirable for many

applications. The contribution of my work includes definition of perception and the related vision concepts in

mathematical terms, making them amenable for computation in contrast to the common imprecise assertions.

This way several commonly experienced vision phenomena are uniquely modeled, including the common

overlooking of objects in our environment, although the objects are visible. My own personal contribution is

conducting computer experiments in virtual reality that formed the inspiration for establishing the model, as

well as interpreting the results from the mathematical derivations in relation to the common vision concepts

and phenomena. I also verified the approach by means of the applications.

It is emphasized that importance of this accomplishment is that, despite the complexity of human vision,

perception is subjected to model-based quantitative treatment for the first time. This is due to the unique

probabilistic treatment presented in this publication. The work presented is in contrast to the existing verbal

or statistical descriptions in architecture, psychology, or neuroscience that are all inconclusive with respect to

precise treatment of perception. Although visual perception has been subject to scientific study for over acentury, it is interesting to note that it remained mysterious what perception precisely is about, while it

http://bk.tudelft.nl/cid

http://bk.tudelft.nl/cid



eluded mathematical modeling until very recently. Many approaches to perception, in particular in the

domain of psychology and neuroscience, are based on experiment, while underlying theoretical models or

hypotheses are either simplistic, ambiguous or even absent, so that gaining insight into the nature of human

perception from the experiments remains minimal. However, considering that the perception phenomenon is

due to brain processing of retinal photon-reception, it is emphasized that the phenomenon is highly complex.

That is, the same experimenter may have different perceptions of the same environment at different times,

depending on the complexity of the environment, psychological state, personal preferences and so on, not to

mention different vantage points. In particular, it is common experience that when we look at a scene, we arenot aware of the existence of all objects the scene comprises. This implies that, although photons are

impinging on retina forming a retinal image, registration of this information in the human brain, so that it is

remembered shortly afterwards, is not certain. Only part of the visual information is remembered. Due to the

complexity of the brain processes and diversity of environments subject to visual perception, the empiric

approaches to perception yielded merely rudimentary understanding of what perception is, and they did not

explain the uncertainty characterizing perception. The approach presented in this paper resolves this issue by

treating perception as a probabilistic event. This way the awareness for environmental objects is quantified,

so that designers using the presented method are enabled to address perceptual demands with greater

precision and more effectiveness during design.

3. Ciftcioglu, Ö., Bittermann, M.S., Sariyildiz, I.S.: A neural fuzzy system for soft computing. In: Proc. The

26th Annual Meeting of the North American Fuzzy Information Processing Society - NAFIPS'07. IEEE, San

Diego, USA (2007) 489-495

An innovative neural fuzzy system is presented for soft computing in design. The purpose refers in particular

to the precision estimation of the degree of satisfaction of design requirements, while the requirements are

generally not sharply defined. Examples of soft requirements are utility or sustainability. A neural tree

structure is considered with nodes of neuronal type, where Gaussian function plays the role of fuzzy

membership function. The total tree structure effectively works as a fuzzy logic system having system inputs

and outputs. In the system, as result of special provisions, the locations of the Gaussian membership

functions of non-terminal nodes happen to be unity, so that the system has several desirable features; it

represents a fuzzy model maintaining the transparency and effectiveness, while it deals with complexity atthe same time. The research is described in detail and its outstanding merits are pointed out in a framework

having transparent fuzzy modeling properties and addressing complexity issues at the same time. An

application of the model is presented by means of a simple, demonstrative architectural design exercise. The

application indicates the suitability of the method for a wide range of similar applications of technological,

industrial and practical interest. My own personal contribution is the application of the method for use in

architectural design. This refers to the determination of the taxonomic relations that constitute the design

knowledge, as well as the fuzzy membership functions that characterize the relations.

It is emphasized that the importance of the work is due to the unique capability of the method to model soft

expert knowledge, while retaining transparency in the model. Namely, in contrast to artificial neural

networks, the method presented does not learn from examples, but it learns by emulating the logicallyconsistent relations among concepts, as exercised via human mind. This makes the method remarkably

suitable for architectural design applications, where generally few data on relevant cases is available for

knowledge elicitation, while there is an abundance of human expert knowledge available to be put into effect

directly. This is uniquely possible using the method presented in this paper, due to the unique integration of

Gaussian shaped fuzzy logic operations in a neural tree framework. The transparency of the modeling

approach presented outstandingly permits integration of knowledge from different experts or stakeholders

into a unified model, so that this methodology is also essential for effective collaborative design.

4. Bittermann, M.S., : Intelligent Design Objects – A Cognitive Approach for Performance-based Design, PhD

Thesis, Delft University of Technology, Delft, The Netherlands (2009) 249

A cognitive approach for performance-based architectural design is presented. It is based on equipping the

objects that constitute a design with some intelligent behavior, so that they are capable of fulfilling the



designer’s goals with guaranteed success. The guarantee is due to the employment of advanced mathematical

methods, such as optimization and adaptation that are borrowed from the exact sciences as exemplary

interdisciplinary mathematical concepts. Based on a mathematical formulation of the goals and

corresponding solution domains, the design objects identify the best properties for themselves in the presence

of the other objects, so that the likelihood of designer’s satisfaction is maximized. This concept is termed

Intelligent Design Object concept, and it is an emulation of design process in machine form. It is to note that

the work

Intelligent Design Object concept is an important contribution as it demystifies design process to someextent, while this process is highly complex and elusive for modeling. The importance stems from the

generic nature of design, being an intelligent and cognitive phenomenon that occurs in almost any creative

human activity. Therefore the results have relevance in many scientific and engineering areas. The work

manifests my research interest in design emulation using appropriate methods, and it lays the foundation for a

machine cognition approach I intend to develop in the future that may form a basis for a computational

theory of design. As fundamental step in this direction, the Intelligent Object approach can be considered a

formalism of design, and it has some cognitive features, namely identification of relative importance among

abstract objectives by means of a systematic process. That is, the machine induces the knowledge on how

much preference to give to the design objectives respectively, which is a formidable issue to accomplish

when any conventional means are used. Beyond architectural design the Intelligent Object approach is

relevant for decision making in complex problem domains, such as other areas of design and planning,

including urban design, industrial design, and regional planning. It is emphasized that the approach is

generic, and uniquely suitable when the problem includes multiple soft criteria, which is commonly the case

in real-world design applications.

5. Ciftcioglu, O., Bittermann, M.S.: Fusion of perceptions in architectural design, In: Proc. of eCAADe 2013 -

Education and Research in Computer Aided Architectural Design in Europe, September 18-20, 2013, Delft,

The Netherlands (in press)

A method for fusion of perceptions is presented. It is based on the probabilistic treatment of perception

introduced in publication nr. 2 above, where perception quantifies the chance an unbiased observer sees an

environmental object. For objects that are to be perceived from multiple viewpoints, such as a sculpture in a

museum, or a building in its urban context, the probabilistic approach uniquely defines the fusion of

perceptions, and this is addressed in the present paper. The fusion of multi-viewpoint perceptions is

accomplished by carrying out the probabilistic union of events. The computation is presented together with

its geometric implications, which become rather intricate for multiple observers, whereas the computation is

straight forward. The method is exemplified for two applications in architectural design at different scales,

namely interior and urban design, indicating the generic nature as well as the large application potential of

the method. My own personal contribution is to the method development, as well as verification of the

method’s validity by means of the applications.

Simulating perception of an object by multiple observers, or by a single observer from multiple viewpoints is

an important novelty. Namely, the method of quantified union of perceptions has been an unresolved issue uptill now, that is resolved in this presentation. For this purpose abstraction of the perception by means of the

probabilistic computations is necessary, since the precise analysis of the perceptions is a formidable issue

otherwise. This is due to abundant visual scene information in general. The resulting perception information

is valuable information for designers, who generally have to take into account multiple perceptual demands.

The use of perception fusion as constrained design objective has been demonstrated by coupling the method

with a probabilistic evolutionary algorithm performing the constraint optimization. The combination of the

two probabilistic methods is a powerful tool for designers, as it permits treatment of architectural design,

despite its highly constrained nature and involvement of many perception related demands. Although the

examples presented in this paper are rather basic, the method is generic and yields highly appreciable scoring

executions in diverse applications in the areas where perception plays a role, such as architecture, urbanism,

interior and industrial design, as well as robotics.

summaries 5 key papers ms bittermann

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