Artificial Intelligence, a Singular Technology: Paradigms, and Models

Abstract

Artificial intelligence is a real driver of the scientific and technological development, with a difficult horizon to assess. This chapter seeks to give a brief overview of this science and technology in order to understand their present condition and potential in the near future. Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. A challenging horizon to predict, artificial intelligence is a genuine force behind technological and scientific advancement. The chapter tries to analyze the various paradigms, models, and approaches, which has been discoursing artificial intelligence. To this end, the symbolic current, the connectionist model of neural networks, and the fuzzy cognitive maps are studied, to then move on to analyze the so-called computational intelligence, and the sub-symbolic current. From a chronological point of view, three paradigms in the development of artificial intelligence are considered: the initial or mono-block, the current paradigm of distributed artificial intelligence, and the starting paradigm of generative artificial intelligence. The first principally resulted in expert systems, which are quite useful, and the second in multi-agent systems and other models. To make the usage and efficacy of these systems and models clear, several examples are provided. Finally, some information on the efforts being made to try to integrate all current methodologies is provided, and a brief prediction regarding the third paradigm, generative artificial intelligence, is also included.