In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different...In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.展开更多
Based on the theories and approaches in biomechanics, the mechanism and pattern of niche construction were discussed systematically. Through establishing the spatial pattern of niche and its measuring-fitness formula,...Based on the theories and approaches in biomechanics, the mechanism and pattern of niche construction were discussed systematically. Through establishing the spatial pattern of niche and its measuring-fitness formula, and the dynamic system models of single- and two-population with niche construction, including corresponding theoretical analysis and numerical simulation on their evolutionary dynamics of population and the mechanism of competitive coexistence, the co-evolutionary relationship between organisms and their environments was revealed. The results indicate that population dynamics is governed by positive feedback between primary ecological factors and resource content. Niche construction generates an evolutionary effect in system by influencing the fitness of population. A threshold effect exists in single population dynamic system, in dynamic system of two competitive populations, niche construction can lead to alternative competitive consequences, which may be a potential mechanism to explain the competitive coexistence of species.展开更多
Dear Editor,This letter is concerned with the evolutionary dynamics of cooperative strategies in social dilemma situations.Stochastic punishment has been proposed,in which whether an individual acts as a punisher or n...Dear Editor,This letter is concerned with the evolutionary dynamics of cooperative strategies in social dilemma situations.Stochastic punishment has been proposed,in which whether an individual acts as a punisher or not is stochastic and depends on its preference for punishment.Meanwhile,both the cost of punishment and whether a defector would be punished are also stochastic.In previous models,the cost of punishment is considered to be either constant or proportional to the number of individuals to be punished.Furthermore,the hypothesis that all defectors should be penalized is frequently adopted.Actually,some defectors may refrain from being punished due to the presence of noise or the limitation of the punishment cost,and the cost of punishment is also dependent on the number of punishers.Thus,we establish an analytic model of stochastic punishment for infinite and well-mixed populations,investigate the effects of stochastic punishment on the evolution of cooperation,and analyze how to support the evolution of cooperation effectively when the stochastic punishment is possible.The objective of this letter is to design a cooperation-promoting stochastic punishment that will allow the system to evolve to full cooperation.The replicator equations have been used to explore the evolutionary dynamics of cooperation under stochastic punishment,and the conditions under which cooperation is favored by natural selection have been specified.展开更多
基金Project supported by the Doctoral Foundation Project of Guizhou University(Grant No.(2019)49)the National Natural Science Foundation of China(Grant No.71961003)the Science and Technology Program of Guizhou Province(Grant No.7223)。
文摘In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.
基金Project supported by the National Natural Science Foundation of China (No.30470298)the National Social Science Foundation of China (No.04AJL007)
文摘Based on the theories and approaches in biomechanics, the mechanism and pattern of niche construction were discussed systematically. Through establishing the spatial pattern of niche and its measuring-fitness formula, and the dynamic system models of single- and two-population with niche construction, including corresponding theoretical analysis and numerical simulation on their evolutionary dynamics of population and the mechanism of competitive coexistence, the co-evolutionary relationship between organisms and their environments was revealed. The results indicate that population dynamics is governed by positive feedback between primary ecological factors and resource content. Niche construction generates an evolutionary effect in system by influencing the fitness of population. A threshold effect exists in single population dynamic system, in dynamic system of two competitive populations, niche construction can lead to alternative competitive consequences, which may be a potential mechanism to explain the competitive coexistence of species.
基金supported by the National Natural Science Foundation of China(NSFC)(61903080)the Fun-damental Research Funds for the Central Universities(2232023D-26).
文摘Dear Editor,This letter is concerned with the evolutionary dynamics of cooperative strategies in social dilemma situations.Stochastic punishment has been proposed,in which whether an individual acts as a punisher or not is stochastic and depends on its preference for punishment.Meanwhile,both the cost of punishment and whether a defector would be punished are also stochastic.In previous models,the cost of punishment is considered to be either constant or proportional to the number of individuals to be punished.Furthermore,the hypothesis that all defectors should be penalized is frequently adopted.Actually,some defectors may refrain from being punished due to the presence of noise or the limitation of the punishment cost,and the cost of punishment is also dependent on the number of punishers.Thus,we establish an analytic model of stochastic punishment for infinite and well-mixed populations,investigate the effects of stochastic punishment on the evolution of cooperation,and analyze how to support the evolution of cooperation effectively when the stochastic punishment is possible.The objective of this letter is to design a cooperation-promoting stochastic punishment that will allow the system to evolve to full cooperation.The replicator equations have been used to explore the evolutionary dynamics of cooperation under stochastic punishment,and the conditions under which cooperation is favored by natural selection have been specified.
文摘针对樽海鞘群优化算法(SSA:Salp Swarm Algorithm)在求解特征选择问题时存在易陷入局部最优、收敛速度慢的不足,基于樽海鞘群优化算法提出了新的改进算法差分进化樽海鞘群特征选择算法(DESSA:Differential Evolution Salp Swarm Algorithm)。DESSA中采用了差分进化策略替代平均算子作为新的粒子迁移方式以增强搜索能力,并加入进化种群动态机制(EPD:Evolution Population Dynamics),加强收敛能力。实验中以KNN(K-Nearest Neighbor)分类器作为基分类器,以UCI(University of California Irvine)数据库中的8组数据集作为实验数据,将DESSA与SSA同具有代表性的算法进行对比实验,实验结果表明,DESSA算法各考察指标较原算法有明显提升,较其他算法相对优越。
