Learning-oriented simulations and applications of self-organization principle

The paper´s objective is to present the result of learning and evolution oriented self-organization simulation model, which could perform valuable solutions in both theoretical and application area. Complexity of systems can be simulated by the given three-layer framework and algorithms, which implement not only interactive behavior mode, but also evolution possibilities on the base of the acting entity information structures. Self-adaptive behaviors are clearly discovered and explored during the simulation procedure. It could be a meaningful theory contribution in system science, and additionally, felicitous combination of the model with application decision problems obtains synchronous decision result within simulation time