Uncertainty measurement with belief entropy on the interference effect in the quantum-like Bayesian Networks

Abstract

Social dilemmas have been regarded as the essence of evolution game theory, in which the prisoner's dilemma game is the most famous metaphor for the problem of cooperation. Recent findings revealed people's behavior violated the Sure Thing Principle in such games. Classic probability methodologies have difficulty explaining the underlying mechanisms of people's behavior. In this paper, a novel quantum-like Bayesian Network was proposed to accommodate the paradoxical phenomenon. The special network can take interference into consideration, which is likely to be an efficient way to describe the underlying mechanism. With the assistance of belief entropy, named as Deng entropy, the paper proposes Belief Distance to render the model practical.Tested with empirical data, the proposed model is proved to be predictable and effective.

An interval‐valued exceedance method in MCDM with uncertain satisfactions

“…represents the interval number that the satisfaction of the alternative is at least S j . The specific rules for interval-value summation are shown in Equation (5).…”

“…Multicriteria decision‐making (MCDM) is an important part of modern decision‐making science, which is also widely used in many fields, such as supplier selection, medical diagnosis, sensor fusion, uncertainty modeling, risk analysis, reliability, and so forth . Many effective techniques have been used in solving MCDM problems, such as intuitionistic fuzzy sets, soft sets, evidence theory, evidential reasoning, D number, and Z number .…”

A new probability transformation method based on a correlation coefficient of belief functions

“…The Dempster-Shafer theory is an effective tool to express uncertainty information and make information fusion. [20][21][22][23] The research related to the Dempster-Shafer theory 1,2 has attracted much interest, including uncertainty measure, 24,25 evidential network, 26,27 evidence combination, [28][29][30] conflict management, 31,32 likelihood function, 33,34 and so on. [35][36][37] On the basis of the Dempster-Shafer theory, many new models handling uncertainty information have also been proposed, like D numbers.…”

Extension of Yager's negation of a probability distribution based on Tsallis entropy

“…The probability distribution function is a useful tool to model the uncertain information, and it has been applied in plenty fields including information fusion, target recognition, and so forth. The probability (belief) distribution function based on the power set also obtained lots of focuses, such as belief conflict, evolutionary games, supplier selection, and failure mode and effects analysis, prediction, and decision making .…”