Artificial Intelligence and Neural Networks

Artificial Intelligence (AI) is usually defined as the science and engineering of making intelligent machines. AI experts do not confine themselves to practice and bring into question the very nature of intelligence. To win this intellectual and scientific challenge, AI experts should be backed by a solid theoretical base in particular Theoretical Computer Science (TCS) should furnish the notions necessary to explore the advanced properties of machines. Unfortunately this support does not seem to be adequate to the scopes. TCS illustrates every aspect of the computer system by means of formal theories although these theories are narrow, disjoined and abstract. How can AI experts answer profound questions about intelligence when the views of the computer and the brain prove to be fragmentary and insufficient? As an assumption how a unifying scientific theory begins with a simple concept and details all the phenomena occurring in the field through an inferential process. Step by step the theory justifies technical achievements and natural events. For example, mechanics is a unified body of knowledge that introduces the concept of speed. Then experts derive the notion of acceleration from it, in turn the notion of force, work, energy and so forth. A set of interconnected conclusions illustrates the entire domain and disentangles any conundrum through deductive reasoning. The structure of a theoretical construction in engineering and science has nothing to do with philosophy. Frame which kept forward, begins with the formal definition of the elementary piece of information which as assumed distinguishable and meaningful.