Creating Chance by New Interactive Evolutionary Computation: Bipartite Graph Based Interactive Genetic Algorithm

2006 ◽  
pp. 554-564
Author(s):  
Chao-Fu Hong ◽  
Hsiao-Fang Yang ◽  
Leuo-hong Wang ◽  
Mu-Hua Lin ◽  
Po-Wen Yang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Computation ◽  
Bipartite Graph ◽  
Interactive Evolutionary Computation ◽  
Interactive Genetic Algorithm

The Efficiency of Interactive Differential Evolution in Creation of Sound Contents

2013 ◽  
Vol 1 (2) ◽  
pp. 16-27 ◽  
Author(s):  
Makoto Fukumoto ◽  
Ryota Yamamoto ◽  
Shintaro Ogawa
Keyword(s):  
Genetic Algorithm ◽  
Differential Evolution ◽  
Evolutionary Algorithm ◽  
Evolutionary Computation ◽  
Warning Sign ◽  
Interactive Evolutionary Computation ◽  
Interactive Genetic Algorithm ◽  
Fitness Value ◽  
The Creation ◽  
The Difference

Interactive Evolutionary Computation (IEC) is known as an effective method to create media contents suited to user’s preference and objectives. As one of the methods, we have applied Differential Evolution (DE) as evolutionary algorithm in IEC. This study investigated the efficacy of Interactive Differential Evolution (IDE) in comparison with Interactive Genetic Algorithm (IGA). Two listening experiments were conducted to investigate the efficacy: experiment 1 as a creating experiment with IDE and IGA, experiment 2 as a re-evaluating experiment. Target of the creation was warning sign sounds. Eighteen subjects participated in both of the experiments. The result of the experiment 1 showed that IDE overcame IGA, and significant increase of fitness was only observed in IDE. The result of the experiment 2, higher fitness value was observed in IDE, however, the difference between the two conditions was not significant. Parts of the results showed a possibility of IDE to create media contents.

scholarly journals Interactive Genetic Algorithm Oriented toward the Novel Design of Traditional Patterns

Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 36 ◽  
Author(s):  
Jian Lv ◽  
Miaomiao Zhu ◽  
Weijie Pan ◽  
Xiang Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
Surrogate Model ◽  
Mean Squared Error ◽  
Back Propagation ◽  
Interactive Evolutionary Computation ◽  
Interactive Genetic Algorithm ◽  
Novel Design ◽  
Fuzzy Interval

To create alternative complex patterns, a novel design method is introduced in this study based on the error back propagation (BP) neural network user cognitive surrogate model of an interactive genetic algorithm with individual fuzzy interval fitness (IGA-BPFIF). First, the quantitative rules of aesthetic evaluation and the user’s hesitation are used to construct the Gaussian blur tool to form the individual’s fuzzy interval fitness. Then, the user’s cognitive surrogate model based on the BP neural network is constructed, and a new fitness estimation strategy is presented. By measuring the mean squared error, the surrogate model is well managed during the evolution of the population. According to the users’ demands and preferences, the features are extracted for the interactive evolutionary computation. The experiments show that IGA-BPFIF can effectively design innovative patterns matching users’ preferences and can contribute to the heritage of traditional national patterns.

Users' Fuzzy Cognition Knowledge Learning in Interactive Evolutionary Computation and its Application

2011 ◽  
Vol 204-210 ◽  
pp. 245-250
Author(s):  
Guo Sheng Hao ◽  
Xiang Jun Zhao ◽  
Yong Qing Huang
Keyword(s):  
Evolutionary Computation ◽  
Search Space ◽  
Interactive Evolutionary Computation ◽  
Sense Unit ◽  
Knowledge Learning

user in interactive evolutionary computation (IEC) has the characteristic of fuzzy cognition. Based on this, a method to learn users’ fuzzy cognition knowledge is given. The method includes the fuzzy expression of the basic elements of IEC such as search space, population, gene sense unit and so on. Then a method to increase the performance of IEC based on the knowledge of users’ fuzzy cognition is given. The above results enrich the researches of IEC users' cognition.

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