Towards Creative Design Using Collaborative Interactive Genetic

Algorithms

Juan C. Quiroz, Sushil J. Louis, Amit Banerjee, and Sergiu Dascalu

Evolutionary Computing Systems LabDepartment of Computer Science & Engineering

University of Nevada, Reno

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Outline

• Motivation• Computational model of creativity• Design space exploration• IGAP• Experimental Setup• Discussion and Results

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Creativity

• John Gero’s definition of creative designing:– The addition of variables during the design

process has the potential, but does not guarantee, to generate creative content.

• Is collaboration amongst peers sufficient to allow for the potential to produce creative content in designing?

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Motivation

• Design process1. Conceptual design2. Detailed design3. Evaluation4. Iterative redesign

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Conceptual Design

• Subjective evaluation of alternative design concepts– Aesthetics and other subjective criteria

• What is the formula for how designers evaluate subjective criteria?

• Collaborative design

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Collaborative Interactive

Genetic Algorithms

Case study: Floorplans

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Computational Model of Creative Design:Collaborative Interactive Genetic Algorithms

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Design Space Exploration

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IGAP: Interactive GA Peer to Peer

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Individual Visualization

Bedroom

Living RoomEating area

Bathroom

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Collaborative Visualization

User’s Individuals Peers’ Individuals

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Experimental Setup

• Objectives:– Create a floorplan for a 2 bedroom, 1 bathroom

apartment– Bathrooms close to the bedrooms– Bathrooms far from kitchen and dining areas

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Experimental Setup

• Participants:– 8 women, 12 men

• Five groups of size four• Agenda

1. Tutorial2. Create individual floorplan3. Create collaborative floorplan4. Evaluation of floorplans

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Evaluation Criteria1. Appealing – unappealing2. Average – revolutionary3. Commonplace – original4. Conventional – unconventional5. Dull – exciting6. Fresh - routine7. Novel – predictable8. Unique – ordinary9. Usual - unusual10. Meets all requirements - does

not meet requirements

• Creative Product Semantic Scale• Seven point likert scale

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Hypothesis

• Is collaboration amongst peers sufficient to allow for the potential to produce creative content in designing?

• Designs evolved collaboratively will consistently rank higher in the evaluation criteria.

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ResultsEvaluation Criterion Desired Ind. Avg. Coll. Avg. P-value

Appealing - Unappealing Low 4.08 4.39 0.439

Average - Revolutionary High 3.76 4.34 0.047Commonplace - Original High 3.97 4.68 0.021

Conventional - Unconventional

High 4.03 4.41 0.355

Dull – Exciting High 3.65 3.93 0.326

Fresh – Routine Low 3.82 3.68 0.810

Novel - Predictable Low 3.55 3.40 0.697Unique - Ordinary Low 3.49 3.11 0.251Usual - Unusual High 4.21 4.51 0.395

Meets All Req. -Does Not Meet Req.

Low 2.63 2.83 0.779

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Preliminary Conclusions

• Collaboration is not sufficient to make a clear distinction between individual and collaborative floorplans (?)

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Observations

• Ambiguity in evaluation criteria– Appealing – unappealing– Positive – Negative (?)– Negative – Positive (?)

• Simple graphic representation

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Observations: A New Hope

• Applicability of evaluation criteria– “Exciting”– Domain expert vs. student

• Participants created only 1 collaborative floorplan and 1 individual floorplan

• Negative effect of viewing entire population– Not enough generations– Not enough sharing

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Conclusions

• Collaborative IGAs as a computational model of creative design

• Floorplans created collaboratively scored higher in “originality” and “revolutionary”– Scores in median range– Graphical representation

• We cannot deduce that collaboration is enough to introduce a creative potential

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Comments/Questions?

• quiroz@cse.unr.edu• www.cse.unr.edu/~quiroz

• Acknowledgements– This work was supported in part by contract number

N00014-0301-0104 from the Office of Naval Research and the National Science Foundation under Grant no. 0447416.