kes iimss 2009: document design with interactive evolution
DESCRIPTION
KES IIMSS 2009 presentation on the use of interactive genetic algorithms for document design. A pretest with three participants is presented with a discussion of affordance issues of interactive evolution.TRANSCRIPT
Document Design with Interactive Evolution
Juan C. Quiroz, Amit Banerjee, Sushil J. Louis, and Sergiu Dascalu
Department of Computer Science & EngineeringUniversity of Nevada, Reno
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Outline
• Motivation• Interactive Genetic Algorithms• Related Work• Evolutionary Document Design• Results• Affordance of Interactive Genetic Algorithms• Future Work
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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?
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Our Goal
• Support a simple design task– Create a brochure document
• Objective requirements• Subjective exploration of designs
• Interactive Genetic Algorithms for exploring brochure document designs
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Background and Related Work
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Genetic Algorithms
• Population based search technique– Natural selection– Survival of the fittest
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Interactive Genetic Algorithms• Human guided evolution• Evaluation of subjective criteria
– Aesthetics– Emotion– Intuition
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Related Work
• Evolution of album page layouts (Geigel and Loui, 2003)
• Album pages are encoded using a 4-tuple for each image in the page:– X, Y, Scaling, Rotation
• User specifies set of preferences at start of GA run– Preference values help guide the evolutionary process
• With IGA, user interacts every generation
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Interactive Document Design
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Evolutionary Document Design• Shapes: rectangles,
ellipses, rounded rectangles
• Shape scaling, along x and y axis, by up to 10%– Scaling up or down
• Shapes can serve as placeholders for content
• Collections of shapes can serve as a background design
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Fitness Evaluation
• Objective heuristics– White space evaluation– Degree of shape overlap– Spatial balance
• Subjective heuristics– Small subset displayed from large population– User evaluation by picking the solution the user likes the
best from the subset– Fitness interpolation of the rest of population based on
similarity to user selected best
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Subjective Evaluation
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Supported Customization• Moving of shapes• Scaling of shapes• Insertion
– Images, Text boxes• Deletion
– Shapes, Text boxes• Color
– Change color scheme– Change individual shape color
• Save to file
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Evolution of BrochuresGeneration 0 Generation 10
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Pretest Experiment
• Three participants• Set of requirements:
– Design a brochure that includes:• A header• At least one paragraph• At least two images
– Brochure to advertise minor in digital interactive games
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Preliminary Sample Brochures
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User Generated Brochures
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Discussion
• All three users were able to create brochures that met the requirements
• Users liked the ability to explore alternative designs
• Interaction with IGA found to be limiting
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Discussion
• Interaction with IGA found to be limiting– Document close to
desired, but users not being able to fine tune the solution by simple picking
– No support for injecting edits made by user back to population
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Discussion
• The ability to view and assess many documents in a few minutes
• Useful when requirements are open-ended– When user has to create
a conceptual model for the given requirements
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Affordance of IGAs
• The designer must make “appropriate actions perceptible and inappropriate ones invisible.” – The Design of Everyday Things
• Typical IGA experience– Maximum of 20 generations– User fatigue– Frustration– Boredom
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Affordance of IGAs
• Most IGA applications s have conceptual models targeted to expert users
• Conceptual model understood only by author researchers
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Affordance Issues in Brochure Evolver
• Picking the best document– Limiting– Reduces user fatigue
• Building a conceptual model of the IGA– End-user should not need an understanding of GAs to use
system• Robustness of evolutionary system
– Is the system working properly?– Is the system performing poorly because it is a hard
problem?
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Future Work
• User studies– Creating brochure from scratch versus using IGA– Difference in quality in designed brochures– Creative Product Semantic Scale as evaluation
criteria• Allow exploration starting with a prototype
brochure
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Conclusions
• Approach to document design based on human guided evolution– In pretest all users were able to generate diverse
brochures that met the given requirements• Limitations in IGA and proposed tool due to
affordance issues