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引用次数: 3

摘要

高峰时段的交通在每个城市都是一个大问题,因此市议会试图鼓励市民选择公共交通工具而不是开车。然而,这种努力被这样一个事实抵消了,即在大多数情况下,旅行者使用汽车的公用事业比乘坐公共汽车的公用事业要多。我们建立了一个交通问题模型,其中有许多智能体,他们有两个选择,根据他们在以前的旅程中获得的效用记忆来选择汽车或公共汽车。用遗传算法模拟这一问题可以研究通勤者的行为,并有助于确定该模型中是否存在纳什均衡。在理论讨论中发现存在纳什均衡,但在模拟过程中种群并不收敛到纳什平衡点。在整个模拟过程中,只有少数旅行者在两种运输方式之间移动以建立动态稳定性,而所有其他人只使用一种运输方式。然而,一些旅行者选择一直使用公共汽车(这增加了整体人口的效用),即使他们的效用相对低于其他旅行者。因此,这些模拟描述了合作的出现,这种合作是建立在一些参与者承担更坏的效用来为所有人获得更多的基础上的。
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Traffic jams: an evolutionary investigation
Traffic at the rush hours is a big problem in every city so that city councils try to encourage citizens to choose mass transportation instead of driving cars. However, this effort is counterbalanced by the fact that travelers' utilities from car usage are more than those from taking buses in most cases. We build a traffic problem model with many agents who have the two options of choosing the car or the bus based on their memory of utilities achieved in previous journeys. Simulating this problem with a genetic algorithm can investigate commuters' behavior and can help identify if a Nash equilibrium exists in this model. We find that a Nash equilibrium exists in theoretical discussion but the population does not converge during the simulation to the Nash equilibrium point. Only a few travelers in the population moved between the two transport methods to establish dynamic stability and all others use only one means of transport throughout the simulation. However, some travelers choose to use the bus all the time (which increases the utilities of the population as a whole) even though their utilities are relatively lower than those of other travelers. Therefore, these simulations describe, the emergence of cooperation which is built on some players bearing worse utilities to obtain more for all the population.
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