Quantum Control Algorithm of Robust KB Self-Organization Process Based on Quantum Fuzzy Inference

Different models of self-organization processes are described from physical, information, and algorithmic (quantum computing) point of view. Role of quantum correlation types and information transport in self-organization of structure type design is discussed. A generalized quantum algorithm (QA) design of self-organization processes is developed. Particular case of this approach (based on early developed quantum swarm model) is discussed. The physical interpretation of self-organization control process on quantum level is introduced based on the information model of the exchange and extraction of quantum (hidden) value information from/between classical particle’s trajectories in particle swarm. New types of quantum correlations (as behavior control coordinator) and information transport (value information) between particle swarm trajectories are introduced. Quantum Fuzzy Inference (QFI) model is introduced based on thermodynamics and information-theoretic measures of agent interactions in communication space between macroand micro-levels (the entanglement-based correlations in an active system represented by a collection of intelligent agents). From computer science viewpoint, QA of QFI model plays the role of the information-algorithmic and SWplatform support for design of self-organization process. Physically, QFI supports optimal thermodynamic trade-off between stability, controllability and robustness in self-organization process. The dominant role of self-organization in robust knowledge base (KB) design of intelligent fuzzy controllers (FC) for unpredicted control situations is discussed.