New Frameworks of Inetractive Evolutionary Computation

5th International Workshop on Computational Intelligence and Applications : uesday, November 10 to Thursday, November 11, 2009 : The Faculty Club at Hiroshima University, Higashi-Hiroshima CampusPSO vs. IGA does not show this tendency. We analyzed them and found that it was due to the too much sensitivity of interactive PSO to quantization noise in fitness. We propose its solutions and show their better performance for less complex tasks than conventional IGA as expected from PSO vs. GA. Tournament IEC requests an IEC user to compare pair individuals, which reduces IEC user fatigue, while conventional IEC requests him/her to compare all individuals and evaluate them to make offspring. Simulated breeding requests his/her to compare all individuals and choose better parents. Although choosing and evaluating look similar, one click for the former and thinking evaluation level relatively and inputting the evaluation level for the latter are quite different from the user fatigue point of view. Drawback of both tournament IEC and simulated breeding are slow conversion due to lack of evaluation information. Paired comparison-based interactive DE has both features of pair comparisons like a tournament IEC and full evaluation like a conventional IEC. Thanks to them, it causes less user fatigue and converges faster. At this moment, this method looks the best IEC framework