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Adaptive and bounded investment returns promote cooperation in spatial public goods games - PubMed

Adaptive and bounded investment returns promote cooperation in spatial public goods games

Xiaojie Chen et al. PLoS One. 2012.

Abstract

The public goods game is one of the most famous models for studying the evolution of cooperation in sizable groups. The multiplication factor in this game can characterize the investment return from the public good, which may be variable depending on the interactive environment in realistic situations. Instead of using the same universal value, here we consider that the multiplication factor in each group is updated based on the differences between the local and global interactive environments in the spatial public goods game, but meanwhile limited to within a certain range. We find that the adaptive and bounded investment returns can significantly promote cooperation. In particular, full cooperation can be achieved for high feedback strength when appropriate limitation is set for the investment return. Also, we show that the fraction of cooperators in the whole population can become larger if the lower and upper limits of the multiplication factor are increased. Furthermore, in comparison to the traditionally spatial public goods game where the multiplication factor in each group is identical and fixed, we find that cooperation can be better promoted if the multiplication factor is constrained to adjust between one and the group size in our model. Our results highlight the importance of the locally adaptive and bounded investment returns for the emergence and dominance of cooperative behavior in structured populations.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Promotion of cooperation due to adaptive and bounded investment returns.

Panel (a) depicts the fraction of cooperators formula image in dependence on the feedback strength formula image for different values of formula image. Panel (b) depicts the fraction of cooperators in dependence on the boundary value formula image for different values of formula image. It can be observed that cooperation can be promoted for large values of feedback strength, and there exist moderate boundary values warranting the best promotion of cooperation. Here, formula image.

Figure 2
Figure 2. Characteristic snapshots of strategy and multiplication factor distributions on a

square lattice during the coevolutionary process. Top row depicts the time evolution (from left to right) of typical distributions of cooperators (grey) and defectors (black) on a square lattice, and bottom row depicts the corresponding time evolution (from left to right) of typical distributions of multiplication factor. Results in all panels are obtained for formula image, formula image, and formula image. We have checked that similar results can emerge for other parameter settings.

Figure 3
Figure 3. Time evolution of average multiplication factor and payoffs.

Panel (a) depicts the time evolution of average values of multiplication factor in the whole population and in the boundary groups, respectively. Panel (b) depicts the time evolution of average payoffs of cooperators and defectors along the boundary, respectively. It can be observed that although the average value of multiplication factor in the whole population is large enough for the evolution of cooperation , the average value along the boundary becomes negative. Correspondingly, the average payoffs of cooperators and defectors along the boundary are both less than zero. As time increases, the average payoff of cooperators along the boundary is a little higher than that of defectors, but has larger fluctuations. Here, formula image, formula image, and formula image.

Figure 4
Figure 4. Cooperation promoted when the values of the lower and upper limits of the investment returns are increased.

Panel (a) depicts the fraction of cooperators in the whole population as a function of time for fixed lower limit formula image and different values of upper limit. Panel (b) depicts the fraction of cooperators in the whole population as a function of time for fixed upper limit formula image and different values of lower limit. Increasing the values of lower and upper limit can provide more positive effects on the evolution of cooperation. Here, formula image and formula image.

Figure 5
Figure 5. Cooperation promoted even when the investment return is updated within the interval.

formula image. Panel (a) shows the fraction of cooperators as a function of formula image for formula image. In this situation, the model recovers to the traditionally spatial PGG, where the multiplication factor in each group is fixed at formula image and formula image. For formula image, cooperators can survive only if formula image, and they can dominate the whole population only if formula image. Panel (b) shows the fraction of cooperators as a function of formula image for fixed formula image and different values of formula image. Initially, the multiplication factor in each interacting group is formula image. Dash lines are used to indicate the critical value of formula image for a better promotion of cooperation in this adaptive and bounded mode for the enhancement factor.

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