Probabilistic linguistic evolutionary game with risk perception in applications to carbon emission reduction decision making

Abstract

Carbon emission reduction, an effective way to facilitate carbon neutrality, has gained increasing attention in government policy and scientific research. However, the establishment of a sustainable carbon emission reduction market is a complex game between governments and enterprises. In addition, it is difficult to obtain precise evaluations of the political and environmental factors in most cases. Irrational enterprises with a profit-seeking nature bring challenges to the strategy selection. To bridge this gap, we propose a probabilistic linguistic evolutionary game to model strategic behavior in carbon emission reduction assistant decision making. First, we introduce a probabilistic linguistic payoff matrix to describe the uncertain payoffs of players. A new distance measure for the probabilistic variables is also proposed to construct the prospect payoff matrix in the prospect theory framework. Then, the evolutionary dynamics and the probabilistic linguistic evolutionary stability of the proposed methods are analyzed. A comprehensive case study for carbon emission reduction with comparisons is presented for validation.