Utility Evaluation Based on One-To-N Mapping in the Prisoner’s Dilemma Game for Interdependent Networks

Abstract

In the field of evolutionary game theory, network reciprocity has become an important means to promote the level of promotion within the population system. Recently, the interdependency provides a novel perspective to understand the widespread cooperation behavior in many real-world systems. In previous works, interdependency is often built from the direct or indirect connections between two networks through the one-to-one mapping mode. However, under many realistic scenarios, players may need much more information from many neighboring agents so as to make a more rational decision. Thus, beyond the one-to-one mapping mode, we investigate the cooperation behavior on two interdependent lattices, in which the utility evaluation of a focal player on one lattice may not only concern himself, but also integrate the payoff information of several corresponding players on the other lattice. Large quantities of simulations indicate that the cooperation can be substantially promoted when compared to the traditionally spatial lattices. The cluster formation and phase transition are also analyzed in order to explore the role of interdependent utility coupling in the collective cooperation. Current results are beneficial to deeply understand various mechanisms to foster the cooperation exhibited inside natural, social and engineering systems.

The detection of faked identity using unexpected questions and mouse dynamics

“…Game theory is also a promising technique in deep learning. We did not evaluate whether more complex deep learning models based on game theory concepts [ 35 – 37 ] could outperform more than standard machine learning models that we used in this research, but it could be a future direction.…”

Safety assessment of petrochemical enterprise using the cloud model, PHA–LOPA and the bow-tie model

“…For example, Wang et al . [ 22 ] discussed the evolution of cooperative behaviour on two interdependent lattices in which the utility evaluation not only concern himself, but also integrate the pay-off information of several corresponding players.…”

Doubly effects of information sharing on interdependent network reciprocity

“…Meanwhile the information available within one network may be helpful to make a decision for the players inside another network, which becomes more obvious in the realm of evolutionary games on networks [27,28] since the players need to maximize their utility through the strategy competition based on their success in previous game rounds. However, most works implement the network interdependence by coupling the individual payoff on different networks and the resilience of cooperation can be largely enhanced by means of the non-trivial organization of players across different networks [53][54][55][56][57][58][59][60][61][62][63].…”

“…In fact, there always exists the errors during the information transmission due to the noise or interference. In addition, many previous works deal with the evolution of cooperation by playing the identical games (say, prisoner's dilemma game (PDG) or snowdrift game (SDG)) on multiple interdependent networks [53][54][55][56][57][58][59][60][61][62][63], and less works consider the situation where the players may perform the distinct game behaviors within different networks or populations. Although Santos et al [65] investigated the evolutionary dynamics of two games within distinct layers of interdependent networks, they leverage a biased strategy imitation process among players which allows the individual on one layer to adopt the strategy of players on the other layer, but there are also some scenarios which do not permit the players to pass on the strategy between different networks.…”