Machine Learning for Human Decision Making with Application of Quantum Probability Theory

The prime concern of the artificial intelligence field would always remain related to the refinement issue. There are several ways to improve the existing machine learning algorithms such as different computation approaches or data model modifications. The success of quantum physics has influenced other sciences significantly, as it helps to understand many peculiar phenomena. The human decision making filed is not an exception. Since the high performance computations are tightly connected to the development of quantum computer, the present paper will focus on the model alteration of data specification. Seemingly irrational human decisions can be explained by the quantum probability theory. Such quantum effects as the interference, the order effect and the observer effect also occur in the human cognition. Mathematical model of quantum theory will help to develop a quantum data model for machine learning. The produced algorithm is expected to be more precise in terms of decision making. The content of the present paper concentrates on the search of the presence of the quantum order effect in the process of human decision making.