MODELING AND ARTIFICIAL INTELLIGENCE

Abstract

Abstract The field of artificial intelligence ( AI) is concerned with improving the understanding of the nature of concepts such as knowledge, intelligence, and consciousness. In the development of the field, modeling the environment has emerged as a central task. Modeling in this sense is a broad term embracing three evolutionary levels: an early stage of biochemical structures, a middle stage in which neural systems emerge, and the later conceptual stage characterized by the use of symbolic structures such as language, interpreted images, and signs. Although AI is particularly concerned with specific area of symbolic knowledge processing, that of logical and relational knowledge, central efforts in this field are also directed at integrating all forms of symbolic modeling into effective solutions for knowledge processing on computers. Thus, methods from computer science are of major importance. This paper illustrates the integration of various forms of modeling within the field of AI. It also shows how a broad concept of modeling enriches AI, and how AI, in turn, brings a new emphasis and understanding of the concept of modeling into science.