1. A method for training a system to specifically react on a specific input, comprising: defining a set of binary data structures, whereas each data structure represents an abstract description of a certain type of a real-world component, item or a virtual object, comprising the features of said type of component, item or object per se, its possible states, its attributes, possible actions to be performed, and possible relationships between said components, items or virtual objects; storing each of the data structures directly as a binary pattern in a computer memory or a disk memory; creating uniquely identifiable copies of the binary data structures to represent an individual instance of said types of components, items or virtual objects; creating a virtual state space of said individual types of components, items or virtual objects by grouping them as relevant for the specific situation; receiving via keybord input, sensor devices or other technical means changes of status or attribute values of at least one of said components, items or virtual objects; storing said received changes as a new version of the respective data structure, representing the changed status and transition process of said individual components, items or virtual objects; analyzing similarities of said binary patterns stored in said computer or disk memory related to a particular action performed; searching for a match in said binary patterns of said data structures; and if at least one repeating binary pattern of said data structures is identified, at least one possible action related to the matched binary pattern is proposed to an operator or performed automatically.