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Altruistic Behavior in Complex Network Based on Reputation and Future Expectation

机译:基于声誉和未来期望的复杂网络利他行为

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According to game theory, the altruistic behavior on complex network is researched by a mechanism Based on reputation and future expectation we proposed. As the information of players' historical behavior, reputation is an important foundation while players choose opponent. The players not only consider current payoff but also care about future payoff when they employ strategy. Simulations and analyses show players choose cooperation voluntarily for the purpose of payoff-maximizing. The level of convergence average reputation of group does not rely on the level of initial average reputation of group. The group can converge to full cooperation even though the initial average reputation of group is small. In a certain interval, a slight increase of the initial average reputation of group can effectively increase the level of cooperation of group. In addition, we found complex network has a certain ability to resist disturbance by simulating the non-subjective factors exist in the real world. Concentrating on the situation of group state changes from cooperative to defective, dynamic spatial patterns show shortcuts are the main reason of the emergence of new defective clusters under the mechanism.
机译:根据博弈论,提出了一种基于声誉和未来期望的机制研究复杂网络上的利他行为。作为玩家历史行为的信息,声誉是玩家选择对手的重要基础。玩家在采用策略时不仅考虑当前的收益,而且还关心未来的收益。仿真和分析显示,参与者出于收益最大化的目的自愿选择合作。组的收敛平均声誉水平不依赖于组的初始平均声誉水平。即使小组最初的平均声誉很小,也可以收敛到全面合作。在一定的时间间隔内,组的初始平均声誉的略微提高可以有效地提高组的合作水平。此外,通过模拟现实世界中存在的非主观因素,我们发现复杂网络具有一定的抵抗干扰能力。着眼于群体状态从合作状态转变为缺陷状态的情况,动态空间格局显示捷径是该机制下新缺陷簇出现的主要原因。

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