Science and Information Conference 2014 August 27-29, 2014 | London, UK 1 | Page www.conference.thesai.org Artificial Intelligence Theory (Bɚsic concepts) Vitaliy Yashchenko Artificial intelligence. Institute of Mathematical Machines and System Problems NANU, IMMSP, Kiev, Ukraine, vitaly.yashchenko@gmail.com Abstract— Taking the bionic approach as a basis, the article discusses the main concepts of the theory of artificial intelligence as a field of knowledge, which studies the principles of creation and functioning of intelligent systems based on multi-layer neural-like growing networks. The general theory of artificial intelligence includes the study of neural-like elements and multi- layer neural-like growing networks, temporary and long-term memory, study of the functional organization of the “brain” of the artificial intelligent systems, of the sensor system, modulatory system, motor system, conditioned and unconditioned reflexes, reflector arc (ring), motivation, purposeful behavior, of “thinking”, “consciousness”, “subconscious and artificial personality developed as a result of training and education”. Keywords—bionic approach; multi-layer neural-like growing networks; sensory system; modulatory system; motor system; conditioned and unconditioned reflex; reflex arc I. INTRODUCTION This work briefly discusses the basic concepts of the theory of artificial intelligence based on multi-layer receptor- effector neural-like growing networks. "Analysis of the problems in the field of artificial intelligence shows that at present time, on the one hand, intensive division of its subfields continues, while on the other hand, one may perceive certain integration of research in an endeavor to build a general theory. Integration of research is forced by the necessity to consolidate the whole research system in the field of artificial intelligence into a single unit, based on a universal concept or idea, aspiring to its functional prototype: intelligent and functional human being" [1]. In artificial intelligence theory such universal concept is represented by multi-layer receptor-effector neural-like growing networks, which aspire to their functional prototype - biological neural networks. II. BASIC CONCEPTS OF ARTIFICIAL INTELLIGENCE A. Artificial intelligence Artificial intelligence - Тs ɚ ПТОlН oП knoаledge, which studies the structure and functioning of intelligent systems based on multi-layer receptor-effector neural-like growing networks. Artificial intelligence theory includes the study of neural-like growing elements and multi-layer neural-like growing networks, temporary and long-term memory, the study of the functional organization of the "brain" of the artificial intelligent systems, of sensory system, modulatory system, motor system, conditioned and unconditioned reflexes, reflector arc, motivation, purposeful behavior, of "reasoning", "consciousness", "subconscious and artificial personality developed as a result of learning and training". Axiom 1. Artificial intelligence theory is based on the analogy with the nervous system of human. The core of human intelligence is the brain, consisting of multiple neurons interconnected by synapses. Interacting with each other through these connections, neurons create complex electric impulses, which control the functioning of the whole organism and allow recognition, learning, reasoning, structuring of information through its analysis, classification, location of connections, patterns and distinctions in it, associations with similar information pieces etc. [2]. The functional organization of the brain. In the works of physiologists P.K. Anohin, A.R. Luriya, E. N. Sokolov [3, 4] and others the functional organization of the brain includes different systems and subsystems. The classical interpretation of the interactive activity of the brain can be represented by interactions of three basic functional units: 1) information input and processing unit - sensory systems (analyzers); 2) modulating, nervous system activating unit - modulatory systems (limbic-reticular systems) of the brain; 3) programming, activating and behavioral acts controlling unit - motor systems (motion analyzer). Brain sensory systems (analyzers). Sensory (afferent) system is activated when a certain event in the environment affects the receptor. Inside each receptor the physical factor affecting it (light, sound, heat, pressure) is converted into an action potential, nervous impulse. Analyzer is a hierarchically structured multi-layer system. Receptor surface serves as the base of the analyzer, and cortex projection areas as its node. Each level is a set of cells, whose axons extend to the next level. Coordination between sequential layers of analyzers is organized based on divergence/convergence principle. Brain modulatory systems are an instrument of regulation of the level of activity, performing also selective modulation, and stressing urgency of a certain function. The initial source of activation is intrinsic activity and the needs of the organism. A second source of activation is related to environmental irritants.