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Lossless geometry compression through changing 3D coordinates into 1D
Yongkui Liu, Lijun He, Peng-jie Wang, Linghua Li, Borut Žalik, 2013, original scientific article

Abstract: A method of lossless geometry compression on the coordinates of the vertexes for grid model is presented. First, the 3D coordinates are pre-processed to be transformed into a specific form. Then these 3D coordinates are changed into 1D data by making the three coordinates of a vertex represented by only a position number, which is made of a large integer. To minimize the integers, they are sorted and the differences between two adjacent vertexes are stored in a vertex table. In addition to the technique of geometry compression on coordinates, an improved method for storing the compressed topological data in a facet table is proposed to make the method more complete and efficient. The experimental results show that the proposed method has a better compression rate than the latest method of lossless geometry compression, the Isenburg-Lindstrom-Snoeyink method. The theoretical analysis and the experiment results also show that the important decompression time of the new method is short. Though the new method is explained in the case of a triangular grid, it can also be used in other forms of grid model.
Keywords: triangular mesh, model, lossless, compression
Published in DKUM: 12.07.2017; Views: 1844; Downloads: 382
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Beyond pairwise strategy updating in the prisoner's dilemma game
Xiaofeng Wang, Matjaž Perc, Yongkui Liu, Xiaojie Chen, Long Wang, 2012, original scientific article

Abstract: In spatial games players typically alter their strategy by imitating the most successful or one randomly selected neighbor. Since a single neighbor is taken as reference, the information stemming from other neighbors is neglected, which begets the consideration of alternative, possibly more realistic approaches. Here we show that strategy changes inspired not only by the performance of individual neighbors but rather by entire neighborhoods introduce a qualitatively different evolutionary dynamics that is able to support the stable existence of very small cooperative clusters. This leads to phase diagrams that differ significantly from those obtained by means of pairwise strategy updating. In particular, the survivability of cooperators is possible even by high temptations to defect and over a much wider uncertainty range. We support the simulation results by means of pair approximations and analysis of spatial patterns, which jointly highlight the importance of local information for the resolution of social dilemmas.
Keywords: cooperation, social dilemma, wisdom of crowds, phase transitions, physics of social systems
Published in DKUM: 23.06.2017; Views: 909; Downloads: 341
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Win-stay-lose-learn promotes cooperation in the spatial prisoner's dilemma game
Yongkui Liu, Xiaojie Chen, Lin Zhang, Long Wang, Matjaž Perc, 2012, original scientific article

Abstract: Holding on to one's strategy is natural and common if the later warrants success and satisfaction. This goes against widespread simulation practices of evolutionary games, where players frequently consider changing their strategy even though their payoffs may be marginally different than those of the other players. Inspired by this observation, we introduce an aspiration-based win-stay-lose-learn strategy updating rule into the spatial prisoner's dilemma game. The rule is simple and intuitive, foreseeing strategy changes only by dissatisfied players, who then attempt to adopt the strategy of one of their nearest neighbors, while the strategies of satisfied players are not subject to change. We find that the proposed winstay-lose-learn rule promotes the evolution of cooperation, and it does so very robustly and independently of the initial conditions. In fact, we show that even a minute initial fraction of cooperators may be sufficient to eventually secure a highly cooperative final state. In addition to extensive simulation results that support our conclusions, we also present results obtained by means of the pair approximation of the studied game. Our findings continue the success story of related winstay strategy updating rules, and by doing so reveal new ways of resolving the prisoner's dilemma.
Keywords: social dilemmas, prisoner's dilemma, cooperation, networks
Published in DKUM: 19.06.2017; Views: 1184; Downloads: 350
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Adaptive and bounded investment returns promote cooperation in spatial public goods games
Xiaojie Chen, Yongkui Liu, Yonghui Zhou, Long Wang, Matjaž Perc, 2012, original scientific article

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.
Keywords: cooperation, public goods, social dilemmas, physics of social systems
Published in DKUM: 19.06.2017; Views: 1040; Downloads: 406
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