Programming the mind and decrypting the universe — A bipolar quantum-neuro-fuzzy associative memory model for quantum cognition and quantum intelligence
Wen-Ran Zhang · 2017
Extending a geometrical and logical unification of mind, light, and matter, a bipolar Quantum-Neuro-Fuzzy Associative Memory (QNFAM) model is proposed for equilibrium-based Quantum Cognition and Quantum Intelligence (QC&QI). It is argued that the brain is neither an electric power machine nor a digital computer, but a dynamic equilibrium of neuron ensembles of bipolar quantum agents. Thus, neuronal electrical signals are inadequate for QC&QI due to their incurred loss of dynamic equilibrium information. On the other hand, it is pointed out that the illogical aspect of quantum mechanics prevents quantum computing from lending itself as an analytical paradigm for equilibrium-based QC&QI. QNFAM is proposed to bridge the gap. Equilibrium and non-equilibrium conditions of QNFAM are identified and axiomatically proved. It is illustrated that QNFAM leads to QC&QI - an equilibrium-based super symmetrical and analytical unification of logical, physical, biological, social, and mental systems for Programming the Mind and Decrypting the Universe.