Co-generative 3D Form: The Framework of
Co-generative Design System
Pi-Yuan
Tang
Graduate Institute of
Architecture, National Chiao Tung University, Hsinchu, Taiwan.
e-mail: yuanc@arch.nctu.edu.tw
Abstract
Generative
design system develops
the purpose that is can generate a large number of design plans. Generative design system can let designer
unceasingly explore the new design plans.
At present generative
design system, they all only have one kind of generative mechanism. Therefore, one can’t provide enough feasibility for designer to explore
new plans. So, in this paper, we propose a framework of Co-Generative Form
System (COgenForm). COgenForm is a 3D form exploration system that
invokes two set of generative mechanisms. This system used co-evolutional
characteristics to build the steps and framework of co-generative design process.
This system includes two groups of generative mechanisms and these will evolve
and interact with each other. Using this system, the form exploration and
generation process can be more dynamic and more alternatives.
Generative design system offers an important mechanism for combining both design generation and computation
mechanism. But, most of generative design systems developed require either well-defined
design problems or the design knowledge embedded should be logical
sound.
This limitation with its computational strength allows generative
mechanism to be explored with logical expression and operation such as SEED project [1, 2]. In addition, generative design system
can also take advantage of current artificial intelligence trend such as
genetic algorithms and then generate form and shape anonymously, such as GENR8 [3] and Agency-GP [4] with evolutionary agent-based mechanism
One thing for sure is the generative mechanism will be the keys for
generating design as well the representation (or exploration metaphor and design
rules) for the generated
design. Different generative mechanism and representation will generate
different design alternatives. Among those, two main generative mechanisms often mentioned
are evolutionary-based
mechanisms and symbol-based
mechanisms.
Most of the current research trend regarding of generative
design system is focusing only one generative mechanism. This makes the
development simplified and computable. On the other hand, the trade-off is to
sacrifice the feasibility and inter-relation between different generative
mechanisms. If there is a mechanism that can incorporate more than one
generative mechanism, the system generated or the design generated by the
system might be closer to design process.
Therefore, in this paper, we proposed a
framework of co-generative design process that can incorporate two different
generative mechanisms and a generative system for form-exploration is proposed
and implemented.
For generative design process model, one mechanism called co-evolution
is adapted for its integration between two diverse evolutionary steps. While
proposed by [5], Maher described
the co-evolution as a cyclic process that sketches the influence between two
species in the natural world. In recent years, the concept of co-evolution has
been applied in different domains, such as co-evolutionary learning [6] and game developing work. The model of
co-evolution design is comprised of three characteristics:
(1) Two design problems extend in parallel way.
(2) Design problems can affect each other via in intercourse way.
(3) One design problem will keep changing while changing another one’s
answers.
General speaking, generative design systems are comprised of four elements: (1) the design
representation (2) a generation engine (3) an expression engine (4) evaluation
and selection mechanism. The generation engine is the main part of the
mechanism of evolving, and new design instance will be generated within the
evolving steps. In this research, we combine these two mechanisms (generative design system and
co-evolution model) into the generative engine and make them affect each other
through the features of co-evolution process. The process that combines these
two mechanisms is called co-generation.
The strategies applied for combining
generative design system and co-evolution model are:
(1) Only have two groups of generative mechanisms in the co-generative
process;
(2) The representation of two mechanisms should be the same or
interchangeable;
(3) Under the same representation, the factors or rules must be
different;
(4) One of generative factors or rules to change that because has
another one;
(5) Using evolutionary
concepts to combine two groups of generative mechanisms, and the generative
factors and rules-like genes. There will
Influence each other like crossover and mutation. We show the co-generative
process in (Figure 1). In this framework we presented main part was co-evolve
mechanism.
Figure 1.
The framework of co-generative process
For testing the computability of our framework of co-generative process, we implement a
design system for the purpose of 3D form exploration. The implementation steps
of a design system using co-generative design process are described as
following.
3.1 The
framework of co-generative design system
In this section, we presented framework of
co-generative design system, in figure 2. In this system include four parts,
representation、generator engine、expression and evaluation
and selection. The main part is generator engine that compiled two mechanisms
and co-evolved each other.
Figure 2.
The framework of co-generative design system.
3.2 The
steps
Three steps are applied for our preliminary implementation are selecting
two three-dimensional form generative mechanisms, developing the
inter-relationship between these two mechanisms, and the selection operators
based on the mechanisms and representation chosen. The details of each step are
described below.
First, two groups of generative mechanisms will be chosen according to
the principles that their representation must be the same or interchangeable.
In addition, each other can generate form by oneself or the other. In this
research, two groups of generative mechanisms set up are L-System mechanism and
Rotate.
Secondly, co-generative design process must be able to let two groups of
generative mechanisms interact with each other in co-generative process. We used the
evolutionary concepts to combine these mechanisms. Generative rules or factors
such as gene are defined and they will interactive with each other through
mutation in the example shown in the example.
Finally, user-controlling strategies the generative process
is divided into two parts: 1) controlling the timeline, and 2) adjusting the
rules and parameters of design. User can also decide when to process the mutation among generative processes, in figure 3. Both two generative mechanisms will keep
generating alternatives according to the set rules until the user stops the
timeline. Once stopped, user can import other generative mechanism to change
the rules or the generative form. Thereafter, the natural selection will be decided according to the user
satisfaction of the results.
Figure 3.
User controlling strategies in co-generative design system.
3.3
Implementation
A co-generative 3D form system called COgenForm is implemented according to the analysis above.
COgenForm is comprised of four elements: (1) Two groups of generative
mechanisms (L-System mechanism and
Rotation mechanism); (2)
Co-generative interaction; (3) Selection operator unit; (4) User interface.
This version of COgenForm is implemented using MEL/Maya. MEL (Maya Embedded
Language) was the main programming language of COgenForm.
4. An example
A housing design is used as the application of COgenForm. The
requirements of this housing design are (1) a 3-bedroom apartment which it
located at Taichung central park; (2) participants
need to discover diverse form strategy for fulfill the function and site
requirements. We provide the
system COgenForm lets a designer with architecture design background to test
this project. The purpose of this housing design is to explore more alternatives and more possibilities with two
parallel logic form generative mechanisms. The
results are shown in Figure 4. It shows two generative processes A and B.
Process A uses L-system and Process B uses rotation features as the mechanism
to generate free form of housing design. The top left window shows the
generation 22 of a sequence of alternatives using L-systems, and the right is
the generation 55. The timeline and parameters of generation process are shown
at the left side of the windows.
Figure 4. Two generative process
that are used L-system and rotate
In Figure 5, we show how combine the two
generative processes with mutation and user controlling. This situation occurs
once designer decide to mutate the design mechanisms. The Generation 82 of
process A is then generated by mutating both mechanism a and mechanism b
based on its parent node.
Figure 5. The co-generative process
with mutation operations
In this paper we present a “co-generative form” framework and generative system called COgenForm. Via the feature of co-evolving, the
generative engine of COgenForm includes two groups of generative mechanisms and
through the influences and stimulation between each other. COgenForm enriches the varieties and possibilities of the children generation and its processes as shown in
example above. Therefore, the inspiring
results that inherit both mechanisms are shown in the display.
By directly manipulating these mechanisms,
designers can discover more alternatives or detours from the original fixed
generation patterns. The computability of applying co-evolution metaphor onto
design generation is clear and useful. As well, as its constraints by the
representation and the mechanisms of it are also unleashed in the paper.
In the future, more generative mechanisms that fulfil the four
requirements of co-generative process can be implemented in COgenForm. And the interfaces
of COgenForm for the users can be evaluated and argued through the refinement
of the system. Hopefully, it
can make the form generated by COgenForm be more inspirable and interesting.
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[2] Flemming, U. and Woodbury, RF.: 1995, Software environment to support early phases in building design (SEED): overview, Journal of Architecture Engineering, 1(4), 147-152.
[3] Hembreg, M., O’Reilly, U. M. and Nordin, P.: 2001, A Design Tool for Surface Generation, Submitted as a late-breaking paper, Genetic and Evolutionary Computation Conference, GECCO 2001.
[4] O’Reilly, U. M., Testa, P., Greenword, S. and Hembreg, M.: 2001, Agency GP: Agent-Based Genetic Programming for Surface Design, Submitted as a late-breaking paper, Genetic and Evolutionary Computation Conference, GECCO 2001.
[5] Maher, M. L. and Poon, J.: 1997, Co-evolution and Emergence in Design, Artificial Intelligence in Engineering, 11(3), 319-327.
[6] Sklar, E., Blair, A. D. and Pollack, J. B.: 1998, in G. Ayala (ed), Workshop on Current Trends and Applications of Artificial Intelligence in Education: Fourth World Congress on Expert Systems, pp. 98-105.