Title
Performance evaluation of interactive evolutionary computation with tournament-style evaluation
Abstract
We describe the effectiveness of interactive evolutionary computation (IEC) with tournament-style evaluation to reduce the evaluation load of IEC users. Most previous studies did not clearly demonstrate the effectiveness of the tournament-style evaluation. Therefore, we implemented a tournament-style evaluation for a specific application and inspected the effectiveness of the IEC with tournament-style evaluation using an experiment with real users. We used three evaluation objects: music, animation, and image. We evaluated the performance of the following three methods. The first was a normal IGA (NIGA), which is a conventional 10-stage evaluation. The second was a tournament-style evaluation with two levels (T2), which evaluates only the superiority or inferiority of two candidates at a time. The third was a tournament-style evaluation with four levels (T4), which progressively evaluates the superiority or inferiority of two candidates. We inspected the effectiveness of these methods by simulation using an evaluation agent that imitated human preferences (or Kansei). The simulation results showed that the evolution performances of the NIGA and T2 are higher than those of the T4. Also, we inspected the effectiveness of these methods by an evaluation experiment with 42 subjects in their 20s. The experiment results showed that the satisfaction level for generated candidates were approximately equal among the NIGA, T2, and T4. Moreover, with the T2, it was easiest for test subjects to evaluate solution candidates than with the NIGA in all evaluation objects. And with the T4, it was easier for test subjects to evaluate solution candidates when the evaluation objects were music and image than with the NIGA.
Year
DOI
Venue
2012
10.1109/CEC.2012.6256128
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
computer animation,evolutionary computation,image processing,multi-agent systems,music,performance evaluation,IEC users,Kansei,NIGA,T2,T4,animation,candidate inferiority,candidate superiority,evaluation agent,evaluation objects,four level tournament-style evaluation,human preferences,image,interactive evolutionary computation,music,normal IGA,performance evaluation,two level tournament-style evaluation
Interactive evolutionary computation,Tournament,Mathematical optimization,Computer science,Image processing,Kansei,Evolutionary computation,Multi-agent system,Animation,Artificial intelligence,Computer animation,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4673-1508-1
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Hiroshi Takenouchi100.34
Tokumaru, M.231.60
Noriaki Muranaka300.34