kes iimss 2009: document design with interactive evolution

Document Design with Interactive Evolution

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

Department of Computer Science & EngineeringUniversity of Nevada, Reno

2

Outline

• Motivation• Interactive Genetic Algorithms• Related Work• Evolutionary Document Design• Results• Affordance of Interactive Genetic Algorithms• Future Work

3

Motivation

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

4

Conceptual Design

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

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

5

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

6

Background and Related Work

7

Genetic Algorithms

• Population based search technique– Natural selection– Survival of the fittest

8

Interactive Genetic Algorithms• Human guided evolution• Evaluation of subjective criteria

– Aesthetics– Emotion– Intuition

9

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

10

Interactive Document Design

11

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

12

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

13

Subjective Evaluation

14

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

15

Evolution of BrochuresGeneration 0 Generation 10

16

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

17

Preliminary Sample Brochures

18

User Generated Brochures

19

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

20

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

21

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

22

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

23

Affordance of IGAs

• Most IGA applications s have conceptual models targeted to expert users

• Conceptual model understood only by author researchers

24

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?

25

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

26

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

27

Questions?

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