1. Interactive Evolutionary Computation As we have seen in this course, EC is a powerful search paradigm. As we have seen in this course, EC is a powerful search paradigm. As long as the user is able to develop an adequate evaluation function, the ECs studied so far will perform well. As long as the user is able to develop an adequate evaluation function, the ECs studied so far will perform well. However, what happens when on cannot develop an evaluation function that is an accurate closed- form mathematical equation? However, what happens when on cannot develop an evaluation function that is an accurate closed- form mathematical equation?

2. Interactive Evolutionary Computation Interactive Evolutionary Computation (IEC) is a welcomed alternative when: Interactive Evolutionary Computation (IEC) is a welcomed alternative when: An accurate evaluation function is difficult to develop, andAn accurate evaluation function is difficult to develop, and The user has an idea of what a good solution may look like.The user has an idea of what a good solution may look like.

3. Interactive Evolutionary Computation IECs have been used for wide variety of applications including [Takagi, H. (2001). “Interactive Evolutionary Computaton: Fusion of the Capabilities of EC Optimization and Human Evaluation”, Proceedings of the IEEE, pp. 1275-1296, Vol. 89, No. 9, September, IEEE Press] : IECs have been used for wide variety of applications including [Takagi, H. (2001). “Interactive Evolutionary Computaton: Fusion of the Capabilities of EC Optimization and Human Evaluation”, Proceedings of the IEEE, pp. 1275-1296, Vol. 89, No. 9, September, IEEE Press] : Graphic Art, Computer Graphics, Animation,Graphic Art, Computer Graphics, Animation, Music,Music, Editorial Design,Editorial Design, Industrial Design,Industrial Design, Face Image Generation,Face Image Generation, Speech Processing,Speech Processing, Hearing Aid Adaptation,Hearing Aid Adaptation, Database Retrieval,Database Retrieval, Data MiningData Mining Image Processing,Image Processing, Robotics,Robotics, etcetc

4. Interactive Evolutionary Computation Not all IECs are the same. There seems to be a continuum. Not all IECs are the same. There seems to be a continuum. EC IntensiveHuman Interaction Intensive Human/EC Collaborative Kennedy, Externalized Particle Swarm Takagi, Lund, etc Parmee

5. Interactive Evolutionary Computation IECs are not just limited to human evaluation. IECs are not just limited to human evaluation. Human evaluation functions are used to provide a fitness for individuals being evolved. Human evaluation functions are used to provide a fitness for individuals being evolved. Instead using human evaluation, human selection (algorithms) can be used. Instead using human evaluation, human selection (algorithms) can be used. Also, human guided procreation has been used in IECs as well. Also, human guided procreation has been used in IECs as well.

6. Interactive Evolutionary Computation Examples

7. Brian Carnahan’s IGA for Anthropomorphic Design (Overcome by Fumes) Brian Carnahan’s IGA for Anthropomorphic Design (Overcome by Fumes)

8. Interactive Distributed Evolutionary Algorithms (IDEAs) Interactive Evolutionary Computation has been shown to be a very powerful technique for solving design problems where the fitness function cannot be expressed as a closed form mathematical equation. Interactive Evolutionary Computation has been shown to be a very powerful technique for solving design problems where the fitness function cannot be expressed as a closed form mathematical equation. Research in the area of Distributed and Parallel Evolutionary Computation has been successfully used to speed up the evolutionary search. Research in the area of Distributed and Parallel Evolutionary Computation has been successfully used to speed up the evolutionary search.

9. Interactive Distributed Evolutionary Algorithms (IDEAs) Therefore, interactive distributed evolutionary computation (IDEC) holds a great deal of promise because: Therefore, interactive distributed evolutionary computation (IDEC) holds a great deal of promise because: Multiple users should be able to design artifacts more quickly than a single user (reducing user fatigue),Multiple users should be able to design artifacts more quickly than a single user (reducing user fatigue), Artifacts developed by multiple users will have a wider range of acceptance,Artifacts developed by multiple users will have a wider range of acceptance, By observing how humans interactively solve problems, we may gain a better understanding (heuristics?) of how to develop ‘intelligent’ ECs.By observing how humans interactively solve problems, we may gain a better understanding (heuristics?) of how to develop ‘intelligent’ ECs.

10. Interactive Distributed Evolutionary Algorithms (IDEAs)

11. An IDEA for Emoticon Design Procedure IDEA_Client{ t = 0; t = 0; Initialize Pop(t) // Randomly Generate 9 Emoticons; Initialize Pop(t) // Randomly Generate 9 Emoticons; Present Pop(t) to User; Present Pop(t) to User; While (Not Done) While (Not Done) { Allow_User_to_Select_An_Emoticon(e); Allow_User_to_Select_An_Emoticon(e); Allow_User_to_Select_A_Mutation_Op(o); Allow_User_to_Select_A_Mutation_Op(o); Send_to_Meme_Space(e); Send_to_Meme_Space(e); Receive_From_Meme_Space(m); Receive_From_Meme_Space(m); Parents(t) = {e, m}; Parents(t) = {e, m}; Offspring(t) = {Create_4_Mutants(e,o); Offspring(t) = {Create_4_Mutants(e,o); Create_3_Recombinants(e,m,o);} Create_3_Recombinants(e,m,o);} Pop(t+1) = Parents(t)  Offspring(t); Pop(t+1) = Parents(t)  Offspring(t); t = t + 1; t = t + 1; }}

12. An IDEA for Emoticon Design http://iis.cse.eng.auburn.edu/~gvdozier/IDEA-1.html http://iis.cse.eng.auburn.edu/~gvdozier/IDEA-1.html http://iis.cse.eng.auburn.edu/~gvdozier/IDEA-1.html

13. An IDEA for Emoticon Design Representation of a Candidate Emoticon Representation of a Candidate Emoticon

14. Experiments For a proof of concept we conduct 3 simple experiments (where Meme Space = 2.5 x # of Networked Users) : For a proof of concept we conduct 3 simple experiments (where Meme Space = 2.5 x # of Networked Users) : Smiley FaceSmiley Face AngerAnger Hand-In-GearHand-In-Gear

15. Results

16. Results: Smiley Face Which is the Best Smiley Face? Which is the Best Smiley Face?

17. Results: Anger Which of these is the Best Anger Emoticon? Which of these is the Best Anger Emoticon?

18. Results: Hand-In-Gear Which of these is the Best Hand-In- Gear Emoticon Which of these is the Best Hand-In- Gear Emoticon

19. Conclusions Our results show that IDEA can be used to allow multiple users to interactively design emoticons. Our results show that IDEA can be used to allow multiple users to interactively design emoticons. Using C4.5, the emoticons can be separated into two groups. The differences between the two groups are statistically significant. Using C4.5, the emoticons can be separated into two groups. The differences between the two groups are statistically significant.

20. Discussion: Why Use an IDEA ? Not All Designers are the Same Not All Designers are the Same StartersStarters Middle RelieversMiddle Relievers Relievers (Finishers)Relievers (Finishers) Not All Designers Work at the Same Pace Not All Designers Work at the Same Pace Not All Designers Have the Same Gifts Not All Designers Have the Same Gifts Some designers may be better critics (selectors)Some designers may be better critics (selectors) Some designers may be more skilled with the evolutionary operatorsSome designers may be more skilled with the evolutionary operators Exploits Design Team Diversity Exploits Design Team Diversity Meme Space: Meme Space: Allows a form of Evolutionary BacktrackingAllows a form of Evolutionary Backtracking Allows more universal ideas to survive longerAllows more universal ideas to survive longer

21. IDEA Questions Some questions concerning the use of IDEAs are as follows: Some questions concerning the use of IDEAs are as follows: Given a design team of N users what is the most effective meme space size?Given a design team of N users what is the most effective meme space size? How do we make sure that faster users don’t overrun the meme space?How do we make sure that faster users don’t overrun the meme space? What is the best composition for a design team?What is the best composition for a design team?

22. Some Questions (cont.) How many designs should one receive from meme space on a given generation?How many designs should one receive from meme space on a given generation? How does this number change over the evolutionary process?How does this number change over the evolutionary process? Should meme space designs be crossed with user selected images?Should meme space designs be crossed with user selected images?

23. Some Questions (cont.) Should the amount of crossover change over the evolutionary process?Should the amount of crossover change over the evolutionary process? How can we detect and reduce user fatigue and frustration?How can we detect and reduce user fatigue and frustration?