A Multi-Level Fusion of Evolutionary Design Processes

1996

An important aspect of creative design is the concept of emergence. Though emergence is important, its mechanism is either not well understood or it is limited to the domain of shapes. This deficiency can be compensated by considering definitions of emergent behaviour from the Artificial Life (ALife) research community. With these new insights, it is proposed that a computational technique, called evolving representations of design genes, can be extended to emergent behaviour. We demonstrate emergent behaviour in a co-evolutionary model of design. This co-evolutionary approach to design allows a solution space (structure space) to evolve in response to a problem space (behaviour space). Since the behaviour space is now an active participant, behaviour may emerge with new structures at the end of the design process. This paper hypothesizes that emergent behaviour can be identified using the same technique. The floor plan example of (Gero & Schnier 1995) is extended to demonstrate how behaviour can emerge in a co-evolutionary design process.

2010

Software used by architectural and industrial designers–has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time.

2013

The evolutionary mode of utilizing today's advance digital technology in architecture is design computing. Spaces, numbers and processes that are conceptualized in architect's mind are algorithmically and mathematically stored on computer systems and used as a generative tool to model building forms. This paper discusses the basic structures of algorithmic architecture based on scripting language Maya Embedded Language and MaxScript. It will tackle how algorithms can be used as generator to concept building forms, and a brief overview of its application to evolutionary design.

As we move away from well-defined problem domains, and get closer to more open-ended domains like planning and design, an increase in the complexity of the problems compel the problem-solving behavior to change in a qualitative sense. Consequently, dynamic problem solving strategies appear as one of the requirements for computational design studies. This paper presents a novel multi-objective Evolutionary Algorithm (EA) called the Interleaved EA (IEA) as a problem-solving tool, which incorporates dynamic aspects. It is specific to IEA that one of the objectives leads the evolution until its fitness progression stagnates. As such, IEA enables the use of different settings and operators for each of its objectives, which would be the same for all objectives in a regular EA. This enables the IEA to dynamically adapt its problem setting throughout its progression. We present the specificities of the IEA with an application on a design problem. As the IEA has been developed to assist in design problems, it is examined through the " Architectural Layout Design " problem studied through library buildings, exemplifying an ill-defined, multi-modal, and multi-objective problem. We compare the functioning of the algorithm with regard to, first, a regular rank-based version, for demonstrating the effect of the leading objective approach; secondly, with a popular multi-objective EA (i.e., NSGA2). We discuss how and why IEA can be used and developed further to incorporate domain specific understanding for multi-modal and dynamic design problems. Keywords: Automated plan layout development; computational architecture; computational design; evolutionary computation in design; evolutionary design.

Applied Intelligence, 2002

Design tools that aim not only to analyse and evaluate, but also to generate and explore alternative design proposals are now under development. An evolutionary paradigm is presented as a basis for creating such tools. First, the evolutionary paradigm is shown to be the only successful design system on which this new phase of design tool could be based. Secondly, any characterisation of design as a search problem is argued to be a serious misconception. Instead it is proposed that evolutionary design systems should be seen as generative processes that are able to evaluate their own output. Thirdly, a generic framework for generative evolutionary design systems is presented. Fourth, the generative process is introduced as a key element within this generic framework. The role of the environment within this process is fundamental. Finally, the direction of future research within the evolutionary design paradigm is discussed with possible short and long term goals being presented.

Proceedings of the 31st International Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe) [Volume 2]

In this paper we examine the potential of combining 2D shape packing algorithms and evolutionary methods in the design process. We investigate the ways such algorithms can be used in architectural design and how they may influence it. In the first part of this paper we introduce the theoretical framework of packing algorithms and genetic algorithms as well as the traditional design process and the nature of design problems. In the second part of the paper we introduce a software prototype that tests these algorithms in two contexts: the preliminary design of a shading façade pattern and the design of commercial housing layouts. The aim for both experiments was to generate optimal configurations based on user-defined criteria without resorting to exhaustive search. Several lessons were learned that point to the potential of evolutionary methods in architecture as well as the limitations of such methods. We conclude the paper with recommendations for further developing this research project.

Abstract. This paper describes an evolutionary search method known as the genetic algorithm (GA) and examines its application to real-world design problems. A description of the algorithm itself and its history is provided. A general review of GA theory and analysis is given, and many of the newer, more advanced types of GA are introduced. Some of the hundreds of different design applications tackled by GAs are then described.

With computational design strategies, particularly evolutionary generative systems, the understanding of the design activity has been changing. Accordingly, the designerly behaviour and the designer's interaction with and the involvement in the design process have been evolving. Evolutionary design systems generate a large number of design solutions that expand design spaces immensely. Especially in multi-modal fitness landscapes, the existence of many optimal design alternatives complicates the designer's cognitive involvement in design. Moreover, particularly in automated design generation, due to the immense expansion in design search space, the designer's visual interaction with the design artifacts is diminished. Accordingly, the proposed research problematizes two major issues of evolutionary design systems; (1) the broad, dense and non-structured design search spaces and (2) the decrease in the designer's involvement in decision-making and evaluation due to the automated design generation. As a solution, perception-based design space structures are proposed as an evaluative structuring strategy. These network structures are intuitive, case-based, observer-dependent and subjective maps of the designer's cognitive world. By encouraging the integration of designer's cognitive abilities in the design synthesis, these structures aim to bridge the gap between the design artefact and the designer by acting as a mediator during the generation process. Alongside, these structures aim to manage the complexity in design search space by providing an environment for designerly evaluation and decision-making. With those aspects, perception-based design space structures are a designer-centric (human-centric) approach for automated design processes and are based on the designer's perception and identification of common visual features. The identification of the common features of instances, visual resemblance is chosen as a criterion for forming perception-based design structures within the scope of this research, on the basis of Rudolph Arnheim's Visual Thinking that highlights forming categories as one of the major ability of a human cognition. Within this scope, a case study is conducted within a group of designers with an existing design space of chairs that are generated by IDEA, an evolutionary system, experimented by Celestino Soddu. In this framework, this paper discusses and presents the experimental study about evolutionary generative design search spaces and perception-based design space structures. Abstract With computational design strategies, particularly evolutionary generative systems, the understanding of the design activity has been changing. Accordingly, the designerly behaviour and the designer's interaction with and the involvement in the design process have been evolving. Evolutionary design systems generate a large number of design solutions that immensely expand design spaces. Especially in multi-modal fitness landscapes, the generation of many optimal design alternatives complicates the designer's cognitive involvement in design. Moreover, particularly in automated design generation, due to the immense expansion in the design search space, the designer's visual interaction with the design artefacts is diminished. The proposed research problematizes two major issues of evolutionary design systems; (1) the broad, dense and non-structured design search spaces and (2) the decreased level of designer involvement in decision-making and evaluation due to the automated design generation. As a solution, perception-based design space structures are proposed as an evaluative structuring strategy. Within this scope, a case study is conducted within a group of designers with an existing design space of chairs that are generated by IDEA, an evolutionary system, experimented by Celestino Soddu. In this framework, this paper discusses and presents the experimental study about evolutionary generative design search spaces and perception-based design space structures.

CAAD Futures ‘95. Singapore, 1995

This paper describes an approach to knowledge representation for an evolutionary design process. The concept of design schemas is introduced to provide the representational framework for design knowledge. Two kinds of design schemas, the design rule schema and the design gene schema, are proposed to formulate design knowledge and interpret the knowledge into genetic codes. A design problem which is used to exemplify this approach is that of a large office layout planning problem.

Summary In its parallel pursuit of an increased competitivity for design offices and more pleasurable and easier workflows for designers, artificial design intelligence is a technical, intellectual, and political challenge. While human-machine cooperation has become commonplace through Computer Aided Design (CAD) tools, a more improved collaboration and better support appear possible only through an endeavor into a kind of artificial design intelligence, which is more sensitive to the human perception of affairs. Considered as part of the broader Computational Design studies, the research program of this quest can be called Artificial / Autonomous / Automated Design (AD). The current available level of Artificial Intelligence (AI) for design is limited and a viable aim for current AD would be to develop design assistants that are capable of producing drafts for various design tasks. Thus, the overall aim of this thesis is the development of approaches, techniques, and tools towards artificial design assistants that offer a capability for generating drafts for sub-tasks within design processes. The main technology explored for this aim is Evolutionary Computation (EC), and the target design domain is architecture. The two connected research questions of the study concern, first, the investigation of the ways to develop an architectural design assistant, and secondly, the utilization of EC for the development of such assistants. While developing approaches, techniques, and computational tools for such an assistant, the study also carries out a broad theoretical investigation into the main problems, challenges, and requirements towards such assistants on a rather overall level. Therefore, the research is shaped as a parallel investigation of three main threads interwoven along several levels, moving from a more general level to specific applications. The three research threads comprise, first, theoretical discussions and speculations with regard to both existing literature and the proposals and applications of the thesis; secondly, proposals for descriptive and prescriptive models, mappings, summary illustrations, task structures, decomposition schemes, and integratory frameworks; and finally, experimental applications of these proposals. This tripartite progression allows an evaluation of each proposal both conceptually and practically; thereby, enabling a progressive improvement of the understanding regarding the research question, while producing concrete outputs on the way. Besides theoretical and interpretative examinations, the thesis investigates its subject through a set of practical and speculative proposals, which function as both research instruments and the outputs of the study. The first main output of the study is the “design_proxy” approach (d_p), which is an integrated approach for draft making design assistants. It is an outcome of both theoretical examinations and experimental applications, and proposes an integration of, (1) flexible and relaxed task definitions and representations (instead of strict formalisms), (2) intuitive interfaces that make use of usual design media, (3) evaluation of solution proposals through their similarity to given examples, and (4) a dynamic evolutionary approach for solution generation. The design_proxy approach may be useful for AD researchers that aim at developing practical design assistants, as has been examined and demonstrated with the two applications, i.e., design_proxy.graphics and design_proxy.layout. The second main output, the “Interleaved Evolutionary Algorithm” (IEA, or Interleaved EA) is a novel evolutionary algorithm proposed and used as the underlying generative mechanism of design_proxy-based design assistants. The Interleaved EA is a dynamic, adaptive, and multi-objective EA, in which one of the objectives leads the evolution until its fitness progression stagnates; in the sense that the settings and fitness values of this objective is used for most evolutionary decisions. In this way, the Interleaved EA enables the use of different settings and operators for each of the objectives within an overall task, which would be the same for all objectives in a regular multi-objective EA. This property gives the algorithm a modular structure, which offers an improvable method for the utilization of domain-specific knowledge for each sub-task, i.e., objective. The Interleaved EA can be used by Evolutionary Computation (EC) researchers and by practitioners who employ EC for their tasks. As a third main output, the “Architectural Stem Cells Framework” is a conceptual framework for architectural design assistants. It proposes a dynamic and multi-layered method for combining a set of design assistants for larger tasks in architectural design. The first component of the framework is a layer-based, parallel task decomposition approach, which aims at obtaining a dynamic parallelization of sub-tasks within a more complicated problem. The second component of the framework is a conception for the development mechanisms for building drafts, i.e., Architectural Stem Cells (ASC). An ASC can be conceived as a semantically marked geometric structure, which contains the information that specifies the possibilities and constraints for how an abstract building may develop from an undetailed stage to a fully developed building draft. ASCs are required for re-integrating the separated task layers of an architectural problem through solution-based development. The ASC Framework brings together many of the ideas of this thesis for a practical research agenda and it is presented to the AD researchers in architecture. Finally, the “design_proxy.layout” (d_p.layout) is an architectural layout design assistant based on the design_proxy approach and the IEA. The system uses a relaxed problem definition (producing draft layouts) and a flexible layout representation that permits the overlapping of design units and boundaries. User interaction with the system is carried out through intuitive 2D graphics and the functional evaluations are performed by measuring the similarity of a proposal to existing layouts. Functioning in an integrated manner, these properties make the system a practicable and enjoying design assistant, which was demonstrated through two workshop cases. The d_p.layout is a versatile and robust layout design assistant that can be used by architects in their design processes.