1. A method for training a system to specifically react on a specific input, comprising: defining a set of data structures, each data structure representing an abstract description of a certain type of a real-world component, item, or virtual object, and each data structure comprising a feature of said represented type of component, item, or object, its possible states, its attributes, its possible actions to be performed, and possible relationships between other of said components, items, or virtual objects; storing each of the data structures in a computer memory or a disk memory; creating uniquely identifiable copies of the 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 a specific situation; receiving in real time data describing a human user's interactions with said real-world components, items, or virtual objects; modifying the virtual state space for the specific situation in response to the human user's interactions; receiving via keyboard 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 data structures stored in said computer or disk memory related to a particular action performed; searching for a match in said data structures; and if at least one matched data structure is identified, proposing or automatically performing at least one possible action related to the matched data structure.