Abstract

In sociology and economics, evolutionary game theory has provided a powerful framework to illustrate the social dilemma’s problems, and many evolutionary game models are presented, such as prisoner’s dilemma game, snowdrift game, public goods game, and so on. In this paper, however, we focus on another typical pair-wise game model: Traveler’s Dilemma Game (TDG), which has been deeply investigated in economics, but less attention has been paid to this topic within the physics community. We mainly discuss the influence of strategy update rules on the evolution of cooperation in the spatial TDG, and in detail explore the role of a novel self-questioning or self-learning update mechanism in the evolution of cooperation of the TDG model on the square lattice. In our self-questioning rule, each player does not imitate the strategy state of his or her nearest neighbors and simply plays the traveler’s dilemma games twice with nearest neighbors: one is to calculate the actual payoff in the current game round; the other is to perform a virtual game which is used to obtain an intangible payoff if he or she adopts another random strategy. Then, the focal player decides to keep the current strategy or to change into that virtual strategy according to the Fermi-like dynamics. A great number of Monte Carlo simulations indicate that our self-questioning rule is a low information game decision-making mechanism which can greatly promote the evolution of cooperation for some specific conditions in the spatial TDG model. Furthermore, this novel rule can also be applied into the prisoner’s dilemma game, and likewise the behavior of cooperation can be largely enhanced. Our results are of high importance to analyze and understand the emergence of cooperation within many real social and economical systems.

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