AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A NOVEL FIELD IN ARTIFICIAL INTELLIGENCE - Arwin Datumaya Wahyudi Sumari; Adang Suwandi Ahmad; Aciek Ida Wuryandari; Jaka Sembiring; Farida Agustini Widjajati (JUTI: Jurnal Ilmiah Teknologi Informasi, 2010)
The essential matter of Artificial Intelligence (AI) is how to build an entity that mimics human intelligence in the way of learning of a phenomenon in a real life to gain knowledge of it and uses the knowledge to solve problems related to it. Based on the findings of intelligenct characteristic displayed by the human brain in growing and generating new knowledge by fusing information perceived by sensory organs, we develop brain-inspired 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. The essential matter of KGS is knowledge-growing method which is based on a new algorithm called Observation Multi-time A3S (OMA3S) information-inferencing fusion method. In this paper we deliver the development of KGS along with some examples of KGS application to a real-life problem. Based on the state-of-the-art of AI and approaches to construct OMA3S method as KG method as well as validations to assess the system performance, we state that brain-inspired KGS is a novel field in AI.