Payoff-dependence learning ability resolves social dilemmas

Understanding the appearance and maintenance of cooperation behavior is one of the most interesting challenges in natural and social sciences. Evolutionary game is a useful tool to study this issue. Here, we consider a basic strategy updating rule: the probability of a player updating its strategy is affected by the learning ability, which is determined by payoffs and an aspiration parameter [Formula: see text]. For positive [Formula: see text], learning ability is directly proportional to player’s own payoff. When [Formula: see text] equals 0, it returns to traditional situation. It is found that increasing the value of [Formula: see text] can promote the cooperation. With the increase of [Formula: see text], the player’s learning ability is continuously enhanced, and the probability of changing strategies is also increased. This paper verifies the influence of the introduced selection parameter [Formula: see text] on the cooperation rate from different aspects. We tested this hypothesis through the Monte Carlo simulation, and demonstrated that introducing [Formula: see text] changed the network of interaction effectively, therefore changing the effect of the adoption of the strategy on the uncertainty of cooperation evolution. This paper analyzed the results of the payoff-dependence learning ability of different players when they imitate the strategies of their opponents, which can effectively promote the evolution of cooperation.

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Optimal Tag-Based Cooperation Control for the “Prisoner’s Dilemma”

Complexity ◽

10.1155/2020/8498613 ◽

2020 ◽

Vol 2020 ◽

pp. 1-19

Author(s):

Rui Dong ◽

Xinghong Jia ◽

Xianjia Wang ◽

Yonggang Chen

Keyword(s):

Social Sciences ◽

Rate Control ◽

Prisoner's Dilemma ◽

Replicator Dynamics ◽

Prisoner’S Dilemma ◽

Evolutionary Process ◽

Evolution Of Cooperation ◽

Optimal Timing ◽

Terminal Time ◽

Cooperation Rate

A long-standing problem in biology, economics, and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. This paper investigates how to promote the evolution of cooperation in the Prisoner’s Dilemma game (PDG). Differing from previous approaches, we not only propose a tag-based control (TBC) mechanism but also look at how the evolution of cooperation by TBC can be successfully promoted. The effect of TBC on the evolutionary process of cooperation shows that it can both reduce the payoff of defectors and inhibit defection; although when the cooperation rate is high, TBC will also reduce the payoff of cooperators unless the identified rate of the TBC is large enough. An optimal timing control (OTC) of switched replicator dynamics is designed to consider the control costs, the cooperation rate at terminal time, and the cooperator’s payoff. The results show that the switching control (SC) between an optimal identified rate control of the TBC and no TBC can properly not only maintain a high cooperation rate but also greatly enhance the payoff of the cooperators. Our results provide valuable insights for some clusters, for example, logistics parks and government, to regard the decision to promote cooperation.

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Using Monte Carlo Simulation in the Social Sciences

Monte Carlo Simulation ◽

10.4135/9781412985116.n4 ◽

2016 ◽

pp. 66-92

Keyword(s):

Social Sciences ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

The Social

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The prisoner’s dilemma game on scale-free networks with heterogeneous imitation capability

International Journal of Modern Physics C ◽

10.1142/s0129183118500778 ◽

2018 ◽

Vol 29 (09) ◽

pp. 1850077 ◽

Cited By ~ 1

Author(s):

Tianhang Wu ◽

Hanchen Wang ◽

Jian Yang ◽

Liang Xu ◽

Yumeng Li ◽

...

Keyword(s):

Evolutionary Game ◽

Prisoner’S Dilemma ◽

Learning Ability ◽

Evolution Of Cooperation ◽

Individual Heterogeneity ◽

Scale Free ◽

Low Degree ◽

Heterogeneous Learning ◽

Scale Free Networks ◽

The Right

In human societies, personal heterogeneity may affect the strategy adoption capability of the individuals. In this paper, we study the effects of heterogeneous learning ability on the evolution of cooperation by introducing heterogeneous imitation capability of players. We design a pre-factor [Formula: see text] to represent the heterogeneous learning ability of players, which is related to the degree of players. And a parameter [Formula: see text] is used to tune the learning levels. If [Formula: see text], the learning ability of players decreases and the low-degree player has the higher reduction level, but if [Formula: see text], the learning ability of low-degree players enhances to a higher level. By carrying out extensive simulations, it reveals that the evolution of cooperation is influenced significantly by introducing player’s heterogeneous learning ability and can be promoted under the right circumstances. This finding sheds some light on the important effect of individual heterogeneity on the evolutionary game.

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Electron Scattering in Solids

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100133618 ◽

1990 ◽

Vol 48 (2) ◽

pp. 4-5

Author(s):

Ryuichi Shimizu ◽

Ze-Jun Ding

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Angular Distribution ◽

Elastic Scattering ◽

Electron Scattering ◽

Cross Sections ◽

Expansion Method ◽

Electron Excitation ◽

Partial Wave Expansion ◽

Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100134922 ◽

1990 ◽

Vol 48 (2) ◽

pp. 264-265

Author(s):

D. R. Liu ◽

S. S. Shinozaki ◽

R. J. Baird

Keyword(s):

Thin Film ◽

Thin Films ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Compound Semiconductors ◽

Energy Dispersive Analysis ◽

X Ray ◽

Metastable Alloys ◽

Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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