Staniszkis, Witold and Staniszkis, Eliza. 2003. Intelligent agent-based expert interactions in
AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A REVIEW ON THE NOVEL FIELD ON ARTIFICIAL INTELLIGENCE
Arwin Datumaya Wahyudi Sumari, A.S. Ahmad, A.I. Wuryandari, J. Sembiring Departemen Elektronika, Akademi Angkatan Udara
Sekolah Teknik Elektro dan Informatika, Institut Teknologi Bandung arwin91aauyahoo.co.id
, asaisrgyahoo.com
, acieklskk.ee.itb.ac.id
, jakadepkominfo.go.id
ABSTRACT
The field of Artificial Intelligence AI has been progressing very advanced since its introduction in 1950s. The essential matter of AI is how to build an entity that mimics human intelligence in the way of
learning of something to gain knowledge of it and use the knowledge to solve problems related to it. In this paper we review a novel field on AI called Knowledge-Growing System KGS that is, a system that is
capable of growing its knowledge along with the accretion of information as the time passes. KGS is developed from our observation of how human’s brain gain new knowledge by fusing information
gathered and delivered by human’s sensory organs. The result of the observation is a new knowledge- growing algorithm called as Observation Multi-time A3S OMA3S information-inferencing fusion
method. Some examples will be delivered to show the application of KGS to real-life problems.
Keywords: AI, information-inferencing fusion, KGS, OMA3S, INTISARI
Bidang Kecerdasan Tiruan telah mengalami kemajuan pesat sejak diperkenalkan pada tahun 1950-an. Hal esensial dari Kecerdasan Tiruan adalah bagaimana membangun suatu entitas yang
menirukan kecerdasan manusia dalam cara pembelajaran terhadap sesuatu untuk meningkatkan pengetahuan tentang sesuatu tersebut dan menggunakan pengetahuan tersebut untuk menyelesaikan
permasalahan-permasalahan yang terkait dengannya. Dalam makalah ilmiah ini kami mengkaji satu bidang baru dalam Kecerdasan Tiruan yang disebut Sistem Berpengetahuan-Tumbuh SBpT yakni
sistem yang memiliki kemampuan untuk menumbuhkan pengetahuannya seiring dengan bertambahnya jumlah informasi seiring dengan berjalannya waktu. SBpT dibangun dari pengamatan terhadap cara otak
manusia dalam memperolah pengetahuan baru dengan cara memfusikan informasi yang dikumpulkan dan dikirimkan oleh panca indera manusia. Hasil dari observasi tersebut adalah algoritma penumbuhan-
pengetahuan baru yang disebut dengan metoda fusi penginferensian-informasi Observation Multi-time A3S OMA3S. Beberapa contoh akan disampaikan untuk memperlihatkan aplikasi SBpT pada
permasalahan-permasalahan di dunia nyata.
Katakunci: Fusi penginferensian-informasi, kecerdasan tiruan, KGS, OMA3S
INTRODUCTION
Building an intelligent entity that is capable of mimicking human intelligence in some aspects has been a challenging research all over the world. Moreover, studies and research in field has been involving
many science and engineering disciplines such as Philosophy, Psychology, Cognitive Science, Computer Science, Mathematics and Engineering as depicted in Figure 1 [1]. Of course, the approaches or
techniques delivered by diverse researchers to emulate human intelligence were difference because they modeled the human intelligence based on their understanding of it combined with the science-and-
engineering bases they had. Refer to [2], McCulloch-Pitts viewed the human intelligence comes from the mechanism occurs in
the human’s nervous system in a model of human brain’s neuron known as Artificial Neural Networks ANN. Lotfi Zadeh saw that human beings do not always think crisply, that is, “yes” or “no”, about a
phenomenon but tend to think in between. Based on this reason he coined Fuzzy Set theory that since then it has been used widely in designing and implementing intelligent-based systems.
Figure 1 : Disciplines of AI
Human beings also have an ability to find the best compromise solution among several given alternatives and it is called as optimization problem. This perspective gave a birth to a new approach
called as Evolutionary Computing where Genetic Algorithm GA is a part of it. Another approach that comes purely from mathematics field is Probabilistic Reasoning PR. The world is very unpredictable
and full of uncertainties. In order that a system can apprehend this situation and solve the problems, it has to deal with these uncertainties.
In solving problems, human being always tries to find the most likely solutions that he has ever experienced in his life. These experiences are stored in his brain in form of knowledge that is grown along
with the accretion of information he sees, hears, etc from his environment as the time goes by. Suppose, he is uncertain with the best available solutions, he will gather or collect more information in order to
obtain comprehensive information regarding the problems. This mechanism is performed repeatedly until he ascertains with the best results to be taken as the basis for making a decision or an action.
The illustration previously described shows that human being gets more intelligence when his knowledge grows from nothing to some extent that makes him able to apprehending the phenomena in his
environment. Knowledge can be grown if there is information delivered to and processed by the brain. The comprehensive information can be obtained by combining or fusing information from all sensory
organs by a technique called information-inferencing fusion. The comprehensive information will become his new knowledge regarding the phenomena he observes. The whole mechanism in obtaining the new
knowledge is called as Knowledge-Growing KG. Our endeavor in this field has come up with an emulation of the KG in human brain called
Knowledge-Growing System KGS with Observation Multi-time A3S OMA3S information- inferencing fusion method as the KG mechanism [3]. Regarding to this matter, the structure of the rest of
the paper is as follows. Section II covers the literatures review regarding to the state-of-the-art of AI research especially that is related to the emulation of how brain obtains new knowledge. In Section III, we
will deliver the development of KGS and followed by Section IV where the examples of KGS application will be presented. The paper converges in Section V with some concluding remarks.
LITERATURES REVIEW
Some literatures reviews have been given in Section I. In this section we focus on two important things that form the KGS namely information fusion and AI. Up to now it is difficult to find literatures
which review the relation between information fusion and AI, even though the essential concept of information fusion itself adopts the mechanism occurred in living things’ brain to obtain more complete
information. Most of the applications of information fusion are for targets tracking and identification with the ultimate aim to deliver comprehensive information for decision-making purposes, see [4] for detail.