Introduction

Abstract

Fundamental aspects of modeling, simulation, optimization, and prediction are available in many sources of literature in the form of scientific papers, books and electronic media that provide living and dynamic foundations for their learning leading to real-life applications. The main purpose of this chapter is not to briefly reflect the content of this book and prepare interested reader directly for most advanced learning principles, but to revise basic knowledge and information taken from the formal education system on the basis of scientific, philosophical, and logical foundations. Shallow learning concepts are presented with their expansions to deep learning methodological modeling, simulation, optimization, and prediction problem solutions through artificial intelligence procedures to achieve rational results that encourage new and innovative directions. The shoots of each topic include categories as possible uncertainties, assumptions and logical rule foundations, dynamic learning principles, “shallow” and “deep” learning foundations and sustainability, safe transition from shallow learning to deep learning environment.