基于PT-MA理论的煤矿安全群体行为演化博弈分析

将前景理论(PT)和心理账户(MA)理论相结合引入到矿工群体、监管群体的演化博弈决策过程中,构建了效价账户和成本账户前景收益感知矩阵,得到不同情况下演化系统所达到的均衡状态,发现当实施安全行为和监管行为与实施对立行为的价值感知收益偏差呈同化正向收敛时,安全行为和监管行为的演化趋于理想状态。但在现实状况下,群体行为演化并不能达到理想的结果,原因如下:(1)安全行为成本、监管行为成本较高,安全行为效价、监管行为效价较低;(2)效价感知函数参照点高,成本感知函数参照点低;(3)矿工、监管群体面对效价收益时更倾向于风险厌恶,面对成本损失时更倾向于风险追求;(4)群体决策更倾向于低估高概率事件(事故概率、监察概率、举报概率)。最后构建Matlab算法,进行演化博弈数值模拟,验证了调节各参数对行为演化的影响作用。本文为煤矿安全监管提供了新的思路,同时对其他领域的安全监管提供了借鉴价值。

Evolutionary Game Analysis of Behaviors of Coal Mine Safety Groups Based on PT-MA Theory

Combining Prospect Theory(PT)and Mental Accounts(MA)theory into the decision-making process of evolutionary game of miner groups and supervision groups, this paper constructs different income prospect sensing matrix from the gain account and pay account to seek the balance of different evolution systems. The paper shows that if the deviations of value perception between the safe supervisory behaviors is positive convergence, the evolution system will be made the optimal state. But the evolution is non-ideal based on the reality of the situation: (1)the safety behavior cost and the supervision cost are high, but the gain of safety behavior and supervision behavior are low; (2)the value of reference point of the gain sensing function is high, but the value of reference point of the pay sensing function is low; (3)miners and supervision groups facing the profits of gain account tend to be risk aversion, but miners and supervision group facing the profits of pay account tend to be risk proneness; (4)group decision-making is more likely to underestimate the high probability event (accident probability, supervision probability and reporting probability) and group behavior evolution does not reach ideal results. The construction of Matlab algorithm of evolutionary game analysis verifies the effect of various parameters on the behavior evolution, and gives new ideas to safety supervision of coal mines and provides reference value for safety supervision in other fields.