A novel trust evolution algorithm based on a quantum-like model of computational trust

Trust models play an important role in decision support systems and computational environments in general. The common goal of the existing trust models is to provide a representation as close as possible to the social phenomenon of trust in computational domains. In recent years, the field of quantum decision making has been significantly developed. Researchers have shown that the irrationalities, subjective biases, and common paradoxes of human decision making can be better described based on a quantum theoretic model. These decision and cognitive theoretic formulations that use the mathematical toolbox of quantum theory (i.e., quantum probabilities) are referred to by researchers as quantum-like modeling approaches. Based on the general structure of a quantum-like computational trust model, in this paper, we demonstrate that a quantum-like model of trust can define a powerful and flexible trust evolution (i.e., updating) mechanism. After the introduction of the general scheme of the proposed model, the main focus of the paper would be on the proposition of an amplitude amplification-based approach to trust evolution. By performing four different experimental evaluations, it is shown that the proposed trust evolution algorithm inspired by the Grover's quantum search algorithm is an effective and accurate mechanism for trust updating compared to other commonly used classical approaches.