When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution...When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.展开更多
We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,w...We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,where agents draw samples from their neighbors and then update their strategies based on conformity or inference according to the situation in the sample.Based on these assumptions,we present the state transition equations in the dynamic evolution of population cooperation,conduct simulation analysis on lattice networks and scale-free networks,and discuss how this mechanism affects the evolution of cooperation and how cooperation evolves under different levels of conformity in the network.Our simulation results show that blindly imitating the strategies of neighbors does not necessarily lead to rapid consensus in the population.Instead,rational inference through samples can better promote the evolution of the same strategy among all agents in the population.Moreover,the simulation results also show that a smaller sample size cannot reflect the true situation of the neighbors,which has a large randomness,and the size of the benefits obtained in cooperation determines the direction of the entire population towards cooperation or defection.This work incorporates the conforming behavior of agents into the game,uses the method of sampling for strategy updates and enriches the theory of evolutionary games with a more realistic significance.展开更多
Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based o...Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper.The algorithm is based on external elite archive and Pareto dominance,and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm.Average entropy and cubic chaoticmapping initialization strategies are proposed to increase population diversity.In the proposed method,we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.Unlike traditional models,this work takes the transmission losses as an optimization target and overcomes complex model constraints through a dynamic relaxation constraint approach.To solve the uncertainty caused by integrating wind and photovoltaic energy in power system scheduling,a multi-objective dynamic environment economical dispatch model is set up that takes the system spinning reserve and network highest losses into account.In this paper,the DE algorithm is improved to form the DGAGE algorithm for the objective optimization of the overall power system,The DE algorithm part of DGAGE is combined with the JAYA algorithm to form the system scheduling HDJ algorithm for multiple energy sources connected to the grid.The effectiveness of the proposed method is demonstrated using CEC2022 and CEC2005 test functions,showing robust optimization performance.Validation on a classical 10-unit system confirms the feasibility of the proposed algorithm in addressing power system scheduling issues.This approach provides a novel solution for dynamic power dispatch systems.展开更多
Individual decision-making processes are not solely driven by self-interest maximization but are also influenced by the pressure to conform to the group.In primary games like the prisoner's dilemma,the presence of...Individual decision-making processes are not solely driven by self-interest maximization but are also influenced by the pressure to conform to the group.In primary games like the prisoner's dilemma,the presence of conformity pressure may facilitate the constructive development of cooperative behavior.In this study,we investigate how conformity influences the growth of cooperation in complicated coordination games.Our findings reveal that,even in the presence of stringent game rules,conformity can promote cooperation.In fact,a certain level of conformity pressure can even eliminate the“defection basin”of deer hunting games played on regular networks.Additionally,we demonstrate that the effect of conformity on cooperative behavior is contingent upon the degree of conformity pressure,with different levels of conformity pressure producing opposite effects.These findings provide novel insights into the promotion of cooperative evolution.For instance,if increasing the reward for cooperation has proven ineffective,manipulating the proportion of initial strategy choices may be a more promising approach.展开更多
In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a r...In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a research hotspot in recent years.In this paper,DRCFJSP with the objective of minimizing the makespan is studied,and it should solve three sub-problems:machine allocation,worker allocation,and operations sequencing.To solve DRCFJSP,a novel hybrid algorithm(CEAM-CP)of cooperative evolutionary algorithm with multiple populations(CEAM)and constraint programming(CP)is proposed.Specifically,the CEAM-CP algorithm is comprised of two main stages.In the first stage,CEAM is used based on three-layer encoding and full active decoding.Moreover,CEAM has three populations,each of which corresponds to one layer encoding and determines one sub-problem.Moreover,each population evolves cooperatively by multiple cross operations.To further improve the solution quality obtained by CEAM,CP is adopted in the second stage.Experiments are conducted on 13 benchmark instances to assess the effectiveness of multiple crossover operations,CP,and CEAM-CP.Most importantly,the proposed CEAM-CP improves 9 best-known solutions out of 13 benchmark instances.展开更多
Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions ac- cording to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new cla...Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions ac- cording to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new class of zero-determinant （ZD） strategies for the repeated games, which can enforce a fixed linear relationship between expected payoffs of two play- ers, indicating that a smart player can control her unwitting co-player＇s payoff in a unilateral way [Proc. Acad. Natl. Sci. USA 109, 10409 （2012）]. The theory of ZD strategies provides a novel viewpoint to depict interactions among players, and fundamentally changes the research paradigm of game theory. In this brief survey, we first introduce the mathematical framework of ZD strategies, and review the properties and constrains of two specifications of ZD strategies, called pinning strategies and extortion strategies. Then we review some representative research progresses, including robustness analysis, cooperative ZD strategy analysis, and evolutionary stability analysis. Finally, we discuss some significant extensions to ZD strategies, including the multi-player ZD strategies, and ZD strategies under noise. Challenges in related research fields are also listed.展开更多
Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optima...Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optimal control is designed for promoting cooperation based on the recent advances in mechanisms for the evolution of cooperation. Two con- trol strategies are proposed： compensation control strategy for the cooperator when playing against a defector and reward control strategy for cooperator when playing against a coop- erator. The feasibility and effectiveness of these control strategies for promoting cooperation in different stages are analyzed. The reward for cooperation can＇t prevent defection from being evolutionary stable strategy （ESS）. On the other hand, compensation for the coopera- tor can＇t prevent defection from emerging and sustaining. By considering the effect and the cost, an optimal control scheme with constraint on the admissible control set is put forward. By analyzing the special nonlinear system of replicator dynamics, the exact analytic solution of the optimal control scheme is obtained based on the maximum principle. Finally, the effectiveness of the proposed method is illustrated by examples.展开更多
The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner＇s games...The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner＇s games in which the players migrate through the success-driven migration mechanism. Numerical simulations illustrate that the strategy continuity promotes cooperation at a low rate of migration, while impeding cooperation when the migration rate is higher. The influence of strategy continuity is also dependent on the game types. Through a more dynamic analysis, the different effects of the strategy continuity at low and high rates of migration are explained by the formation, expansion, and extinction of the self-assembled clusters of ＂partial-cooperators＂ within the gaming population.展开更多
基金supported by the National Natural Science Foundation of China(72471240).
文摘When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.
基金Project supported by the National Natural Science Foundation of China(Grant No.72031009)the National Social Science Foundation of China(Grant No.20&ZD058)。
文摘We study the influence of conformity on the evolution of cooperative behavior in games under the learning method of sampling on networks.A strategy update rule based on sampling is introduced into the stag hunt game,where agents draw samples from their neighbors and then update their strategies based on conformity or inference according to the situation in the sample.Based on these assumptions,we present the state transition equations in the dynamic evolution of population cooperation,conduct simulation analysis on lattice networks and scale-free networks,and discuss how this mechanism affects the evolution of cooperation and how cooperation evolves under different levels of conformity in the network.Our simulation results show that blindly imitating the strategies of neighbors does not necessarily lead to rapid consensus in the population.Instead,rational inference through samples can better promote the evolution of the same strategy among all agents in the population.Moreover,the simulation results also show that a smaller sample size cannot reflect the true situation of the neighbors,which has a large randomness,and the size of the benefits obtained in cooperation determines the direction of the entire population towards cooperation or defection.This work incorporates the conforming behavior of agents into the game,uses the method of sampling for strategy updates and enriches the theory of evolutionary games with a more realistic significance.
基金funded by the Major Humanities and Social Sciences Research Projects in Zhejiang Higher Education Institutions,grant number 2023QN131National Innovation Training Program Project in China,grant number 202410451009.
文摘Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper.The algorithm is based on external elite archive and Pareto dominance,and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm.Average entropy and cubic chaoticmapping initialization strategies are proposed to increase population diversity.In the proposed method,we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.Unlike traditional models,this work takes the transmission losses as an optimization target and overcomes complex model constraints through a dynamic relaxation constraint approach.To solve the uncertainty caused by integrating wind and photovoltaic energy in power system scheduling,a multi-objective dynamic environment economical dispatch model is set up that takes the system spinning reserve and network highest losses into account.In this paper,the DE algorithm is improved to form the DGAGE algorithm for the objective optimization of the overall power system,The DE algorithm part of DGAGE is combined with the JAYA algorithm to form the system scheduling HDJ algorithm for multiple energy sources connected to the grid.The effectiveness of the proposed method is demonstrated using CEC2022 and CEC2005 test functions,showing robust optimization performance.Validation on a classical 10-unit system confirms the feasibility of the proposed algorithm in addressing power system scheduling issues.This approach provides a novel solution for dynamic power dispatch systems.
基金supported by the National Natural Science Foundation of China(Grant No.72031009)the National Social Science Foundation of China(Grant No.20&ZD058)the National Natural Science Foundation of China(Grant No.72101189)。
文摘Individual decision-making processes are not solely driven by self-interest maximization but are also influenced by the pressure to conform to the group.In primary games like the prisoner's dilemma,the presence of conformity pressure may facilitate the constructive development of cooperative behavior.In this study,we investigate how conformity influences the growth of cooperation in complicated coordination games.Our findings reveal that,even in the presence of stringent game rules,conformity can promote cooperation.In fact,a certain level of conformity pressure can even eliminate the“defection basin”of deer hunting games played on regular networks.Additionally,we demonstrate that the effect of conformity on cooperative behavior is contingent upon the degree of conformity pressure,with different levels of conformity pressure producing opposite effects.These findings provide novel insights into the promotion of cooperative evolution.For instance,if increasing the reward for cooperation has proven ineffective,manipulating the proportion of initial strategy choices may be a more promising approach.
基金supported by the Funds for the National Natural Science Foundation of China(Nos.52205529 and 62303204)Natural Science Foundation of Shandong Province(Nos.ZR2021QE195 and ZR2021QF036)+2 种基金Youth Innovation Team Program of Shandong Higher Education Institution(No.2023KJ206)Guangyue。Youth Scholar Innovation Talent Program support received from Liaocheng University(No.LCUGYTD2022-03)Foundation of Young Talent of Lifting engineering for Science and Technology in Shandong,China(No.SDAST2024QTA074).
文摘In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a research hotspot in recent years.In this paper,DRCFJSP with the objective of minimizing the makespan is studied,and it should solve three sub-problems:machine allocation,worker allocation,and operations sequencing.To solve DRCFJSP,a novel hybrid algorithm(CEAM-CP)of cooperative evolutionary algorithm with multiple populations(CEAM)and constraint programming(CP)is proposed.Specifically,the CEAM-CP algorithm is comprised of two main stages.In the first stage,CEAM is used based on three-layer encoding and full active decoding.Moreover,CEAM has three populations,each of which corresponds to one layer encoding and determines one sub-problem.Moreover,each population evolves cooperatively by multiple cross operations.To further improve the solution quality obtained by CEAM,CP is adopted in the second stage.Experiments are conducted on 13 benchmark instances to assess the effectiveness of multiple crossover operations,CP,and CEAM-CP.Most importantly,the proposed CEAM-CP improves 9 best-known solutions out of 13 benchmark instances.
基金supported by the National Natural Science Foundation of China(Grant Nos.61004098 and 11222543)the Program for New Century Excellent Talentsin Universities of China(Grant No.NCET-11-0070)+2 种基金the Special Project of Youth Science and Technology Innovation Research Team of Sichuan ProvinceChina(Grant No.2013TD0006)the Research Foundation of UESTC and Scholars Program of Hong Kong(Grant No.G-YZ4D)
文摘Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions ac- cording to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new class of zero-determinant （ZD） strategies for the repeated games, which can enforce a fixed linear relationship between expected payoffs of two play- ers, indicating that a smart player can control her unwitting co-player＇s payoff in a unilateral way [Proc. Acad. Natl. Sci. USA 109, 10409 （2012）]. The theory of ZD strategies provides a novel viewpoint to depict interactions among players, and fundamentally changes the research paradigm of game theory. In this brief survey, we first introduce the mathematical framework of ZD strategies, and review the properties and constrains of two specifications of ZD strategies, called pinning strategies and extortion strategies. Then we review some representative research progresses, including robustness analysis, cooperative ZD strategy analysis, and evolutionary stability analysis. Finally, we discuss some significant extensions to ZD strategies, including the multi-player ZD strategies, and ZD strategies under noise. Challenges in related research fields are also listed.
文摘Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optimal control is designed for promoting cooperation based on the recent advances in mechanisms for the evolution of cooperation. Two con- trol strategies are proposed： compensation control strategy for the cooperator when playing against a defector and reward control strategy for cooperator when playing against a coop- erator. The feasibility and effectiveness of these control strategies for promoting cooperation in different stages are analyzed. The reward for cooperation can＇t prevent defection from being evolutionary stable strategy （ESS）. On the other hand, compensation for the coopera- tor can＇t prevent defection from emerging and sustaining. By considering the effect and the cost, an optimal control scheme with constraint on the admissible control set is put forward. By analyzing the special nonlinear system of replicator dynamics, the exact analytic solution of the optimal control scheme is obtained based on the maximum principle. Finally, the effectiveness of the proposed method is illustrated by examples.
基金Supported by the National Natural Science Foundation of China(61702076,71371040,71533001,71371040)the Fundamental Research Funds for the Central Universities(DUT17RW131)
文摘The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner＇s games in which the players migrate through the success-driven migration mechanism. Numerical simulations illustrate that the strategy continuity promotes cooperation at a low rate of migration, while impeding cooperation when the migration rate is higher. The influence of strategy continuity is also dependent on the game types. Through a more dynamic analysis, the different effects of the strategy continuity at low and high rates of migration are explained by the formation, expansion, and extinction of the self-assembled clusters of ＂partial-cooperators＂ within the gaming population.
