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Die Seite wurde neu angelegt: „== Reference == Hideyuki Takagi: New Frameworks of Interactive Evolutionary Computation. The 5th International Conference on Computational Intelligence…“

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== Reference ==
[[Hideyuki Takagi]]: [[New Frameworks of Interactive Evolutionary Computation]]. The 5th International Conference on Computational Intelligence & Applications (IWCIA2009), Higashi-Hiroshima, Japan, p.2 (Novemver 10-12, 2009).

== DOI ==

== Abstract ==
First, we discuss one research direction of computational
intelligence (CI) in the 21st Century. Key techniques of CI in
the last Century were neural networks, fuzzy systems, and
evolutionary computation (EC), and they have been used
practically and widely. What comes next? My view is that
human factors become important in/for CI at the beginning of
this century. Imagine consumer robots which market is
expanding in Japan now; cute, interesting, funny, or
emotional behavior are much important for them, while
accuracy and efficiency are the keys for industrial robots.
Such emotional behaviors cannot be designed and controlled
without human evaluation. I am calling this direction as
Humanized Computational Intelligence.

Second, we state that interactive EC (IEC) is one of
approaches to realize the Humanized Computational
Intelligence. Then, we explain what IEC is and how to use it.
The IEC is the EC which evolutionary process is controlled
by human directly. In other words, the fitness function of the
IEC is human itself. Conventional system optimization
requests a numerical target to make a cost function. However,
there are many tasks which performances cannot be measured
objectively but can be evaluated based on human auditory,
vision, or other sensory. The IEC is a good design tool for
these tasks.

We view a wide variety of IEC applications. It includes:
graphic arts and animation, music, editorial design, 3-D CG
lighting, industrial design, facial image generation, speech
processing and synthesis, hearing aid fitting, virtual reality,
media database retrieval, data mining, image processing,
control and robotics, food industry, geophysics, education,
entertainment, social system, environmental engineering,
MEMS design, and therapy.

Third, we turn into to the main topic of this talk: some
new IEC frameworks. Most of the mentioned IEC
applications use conventional interactive genetic algorithms
(IGA) or interactive genetic programming. Here, we
introduce other IEC: interactive Particle Swarm Optimization
(PSO), tournament IGA and simulated breeding, and
interactive differential evolution (DE).

Interactive PSO is an IEC where PSO is used as an EC
part. The complexity of IEC landscape is so simple that IEC
users can find satisfactory solutions with a few population
size and a few searching generations. PSO shows better
performance than GA for simple tasks in general. However,
interactive PSO 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.

== Extended Abstract ==

== Bibtex ==

== Used References ==

== Links ==
=== Full Text ===
http://ir.lib.hiroshima-u.ac.jp/files/public/28434/20141016164413563263/Lecture2-Takagi.pdf one page keynote

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=== Sonstige Links ===

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New Frameworks of Interactive Evolutionary Computation - Versionsgeschichte

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Gbachelier: Die Seite wurde neu angelegt: „== Reference == Hideyuki Takagi: New Frameworks of Interactive Evolutionary Computation. The 5th International Conference on Computational Intelligence…“