Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over p...Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.展开更多
To keep the secrecy performance from being badly influenced by untrusted relay(UR), a multi-UR network through amplify-and-forward(AF) cooperative scheme is put forward, which takes relay weight and harmful factor int...To keep the secrecy performance from being badly influenced by untrusted relay(UR), a multi-UR network through amplify-and-forward(AF) cooperative scheme is put forward, which takes relay weight and harmful factor into account. A nonzero-sum game is established to capture the interaction among URs and detection strategies. Secrecy capacity is investigated as game payoff to indicate the untrusted behaviors of the relays. The maximum probabilities of the behaviors of relay and the optimal system detection strategy can be obtained by using the proposed algorithm.展开更多
Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate...Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.展开更多
In a first for the African continent,Senegal will host the Dakar 2026 Youth Olympic Games(YOG)from 31 October to 13 November.The Dakar 2026 YOG carry a strong symbolic ambition,embodied by their motto“Africa welcomes...In a first for the African continent,Senegal will host the Dakar 2026 Youth Olympic Games(YOG)from 31 October to 13 November.The Dakar 2026 YOG carry a strong symbolic ambition,embodied by their motto“Africa welcomes,Dakar celebrates.”Host Senegal sees the event as a catalyst for its influence,the modernisation of its infrastructure,and the mobilisation of its youth.展开更多
GameQualityAssurance(QA)currently relies heavily onmanual testing,a process that is both costly and time-consuming.Traditional script-and log-based automation tools are limited in their ability to detect unpredictable...GameQualityAssurance(QA)currently relies heavily onmanual testing,a process that is both costly and time-consuming.Traditional script-and log-based automation tools are limited in their ability to detect unpredictable visual bugs,especially those that are context-dependent or graphical in nature.As a result,many issues go unnoticed during manual QA,which reduces overall game quality,degrades the user experience,and creates inefficiencies throughout the development cycle.This study proposes two approaches to address these challenges.The first leverages a Large Language Model(LLM)to directly analyze gameplay videos,detect visual bugs,and automatically generate QA reports in natural language.The second approach introduces a pipeline method:first generating textual descriptions of visual bugs in game videos using the ClipCap model,then using those descriptions as input for the LLM to synthesize QA reports.Through these two multi-faceted approaches,this study evaluates the feasibility of automated game QA systems.To implement this system,we constructed a visual bug database derived from real-world game cases and fine-tuned the ClipCap model for the game video domain.Our proposed approach aims to enhance both efficiency and quality in game development by reducing the burden of manual QA while improving the accuracy of visual bug detection and ensuring consistent,reliable report generation.展开更多
The problem of maneuvering for a servicing spacecraft(inspector)to inspect a noncooperative spacecraft(evader)in cislunar space is investigated in this paper.The evader,which may be a malfunctioning or uncontrolled sa...The problem of maneuvering for a servicing spacecraft(inspector)to inspect a noncooperative spacecraft(evader)in cislunar space is investigated in this paper.The evader,which may be a malfunctioning or uncontrolled satellite,introduces uncertainties due to its potential maneuvering capabilities.To address this challenge,the scenario is modeled as a special orbital game,incorporating the unique complexities of the cislunar environment.A variable-duration,turn-based inspection and anti-inspection game model is designed.The model defines both players'rules,constraints,and victory conditions,providing a framework for non-cooperative inspection.Strategies for both players are developed and validated based on their dynamical properties.The inspector's strategy integrates two-body Lambert transfers with shooting methods,while the evader's strategy aims to maximize the inspector's fuel consumption.Simulation results show that the evader's optimal strategy involves deliberate fluctuations in its lunar periapsis altitude,with the inspector's requiredΔV up to eight times greater than the evader's.The impact of game constraints is evaluated,and the effectiveness of deploying the inspector in low lunar orbit is compared with the inspector at the Earth-Moon Lagrange point L1.The strengths and weaknesses of both are shown.These findings provide valuable insights for future orbital servicing and orbital games.展开更多
In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task exec...In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task execution delay and node energy consumption,and the scheduling and adaptation challenges brought about by device heterogeneity,urgently need to be addressed.To tackle this problem,this paper constructs a multi-objective real-time task scheduling model that considers task real-time performance,execution delay,system energy consumption,and node interests.The model aims to minimize the delay upper bound and total energy consumption while maximizing system satisfaction.A real-time task scheduling algorithm based on bilateral matching game is proposed.By designing a bidirectional preference mechanism between tasks and computing nodes,combined with a multi-round stable matching strategy,accurate matching between tasks and nodes is achieved.Simulation results show that compared with the baseline scheme,the proposed algorithm significantly reduces the total execution cost,effectively balances the task execution delay and the energy consumption of compute nodes,and takes into account the interests of each network compute node.展开更多
Vaccination is a key strategy to curb the spread of epidemics.Heterologous vaccination,unlike homologous vaccination which acts on a single target and forms a single immune barrier,covers multiple targets for broader ...Vaccination is a key strategy to curb the spread of epidemics.Heterologous vaccination,unlike homologous vaccination which acts on a single target and forms a single immune barrier,covers multiple targets for broader protection.Yet,heterologous vaccination involves a complex decision process that conventional game-theoretic approaches,such as classical,evolutionary,and minority games cannot adequately capture.The parallel minority game(PMG)can handle bounded-rational,multi-choice decisions,but its application in vaccine research remains rare.In this study,we propose a vaccination-transmission coupled dynamic mechanism based on the parallel minority game and simulate it on a two-dimensional lattice.Using actual observational data and a mean-field mathematical model,we verify the effectiveness of this mechanism in simulating realistic vaccination behavior and transmission dynamics.We further analyze the impact of key parameters,such as vaccine efficacy differences and the proportion of individuals eligible for vaccine switching,on containment effectiveness.Our results demonstrate that heterologous vaccination surpasses homologous vaccination in containment effectiveness,particularly when vaccine efficacy varies significantly.This work provides a novel framework and empirical evidence for understanding individual decision-making and population-wide immunity formation in multi-vaccine settings.展开更多
An attack-resilient distributed Nash equilibrium(NE) seeking problem is addressed for noncooperative games of networked systems under malicious cyber-attacks,i.e.,false data injection(FDI) attacks.Different from many ...An attack-resilient distributed Nash equilibrium(NE) seeking problem is addressed for noncooperative games of networked systems under malicious cyber-attacks,i.e.,false data injection(FDI) attacks.Different from many existing distributed NE seeking works,it is practical and challenging to get resilient adaptively distributed NE seeking under unknown and unbounded FDI attacks.An attack-resilient NE seeking algorithm that is distributed(i.e.,independent of global information on the graph's algebraic connectivity,Lipschitz and monotone constants of pseudo-gradients,or number of players),is presented by means of incorporating the consensus-based gradient play with a distributed attack identifier so as to achieve simultaneous NE seeking and attack identification asymptotically.Another key characteristic is that FDI attacks are allowed to be unknown and unbounded.By exploiting nonsmooth analysis and stability theory,the global asymptotic convergence of the developed algorithm to the NE is ensured.Moreover,we extend this design to further consider the attack-resilient NE seeking of double-integrator players.Lastly,numerical simulation and practical experiment results are presented to validate the developed algorithms' effectiveness.展开更多
This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint...This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint programming approach is adopted to address uncertainties stemming from renewable generation and load demand within individual VPPs,while robust optimization techniques manage electricity and thermal price volatilities.Building upon this foundation,a hierarchical Nash-Stackelberg game model is established across multiple VPPs.Within each VPP,a Stackelberg game resolves the strategic interaction between the operator and photovoltaic prosumers(PVP).Among VPPs,a cooperative Nash bargaining model coordinates alliance formation.The problem is decomposed into two subproblems:maximizing coalitional benefits,and allocating cooperative surpluses via payment bargaining,solved distributively using the alternating direction method of multipliers(ADMM).Case studies demonstrate that the proposed strategy significantly enhances the economic efficiency and uncertainty resilience of multi-VPP alliances.展开更多
To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public i...To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public is constructed.The operation period is divided into different stages for differentiated analysis.A simulation analysis was performed on the Lituo sinking section of the Beijing-Hong Kong-Macao Highway to assess the impact of variations in critical elements on the system.The results indicate that the Lituo sinking section of the Beijing-Hong Kong-Macao Highway is currently in its early stage of development,with the corresponding strategies being active regulation,excessive emissions,and supervision.When the cost of the government’s active regulation decreases from 1×10^(5) to 5×10^(4) yuan,the system converges more rapidly toward the active regulation strategy.When the cost of the operator’s excessive emissions increases from 14.08×10^(6) to 20.00×10^(6) yuan,the system drives the operator toward the standardized emission strategy.In addition,when the cost of public supervision decreases from 15×10^(4) to 5×10^(4) yuan and the compensation paid by operators to the public increases from 1.288×10^(6) to 2.576×10^(6) yuan,the system converges more quickly toward the supervision strategy.The cost of the operator’s excessive emissions serves as the core decision variable for achieving the ideal equilibrium in the three-party game involving government active regulation,operator standardized emissions,and public supervision.展开更多
In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dyna...In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dynamic fighting scenarios,and exists situations where the scenario and rule of the Colonel Blotto(CB)game are too restrictive in real world.To address these issues,a support stage is added as supplementary for pre-allocated results,in which a novel two-stage competitive resource assignment problem is formulated based on CB game and stochastic Lanchester equation(SLE).Further,the force attrition in these two stages is formulated as a stochastic progress to consider the complex fighting progress,including the case that the player with fewer resources defeats the player with more resources and wins the battlefield.For solving this two-stage resource assignment problem,nested solving and no-regret learning are proposed to search the optimal resource assignment strategies.Numerical experiments are taken to analyze the effectiveness of the proposed model and study the assignment strategies in various cases.展开更多
This paper studies an indefinite mean-field game with Markov jump parameters,where all agents'diffusion terms depend on control variables and both state and control average terms(x.^((N)),u.^((N)))are considered.O...This paper studies an indefinite mean-field game with Markov jump parameters,where all agents'diffusion terms depend on control variables and both state and control average terms(x.^((N)),u.^((N)))are considered.One notable aspect is the relaxation of the assumption regarding the positivity or non-negativity of weight matrices within costs,allowing for zero or even negative values.By virtue of mean-field methods and decomposition techniques,we have derived decentralized strategies presented by Hamiltonian systems and a new type of consistency condition system.These systems consist of fully coupled regime-switching forward-backward stochastic differential equations that do not conform to the Monotonicity condition.The well-posedness of these strategies is established by employing a relaxed compensator method with an easily verifiable Condition(RC)and the decomposition technique.Furthermore,we demonstrate that the resulting decentralized strategies achieve anϵ-Nash equilibrium in the indefinite case without any assumptions on admissible control sets using novel estimates of the disturbed state and cost function.Finally,our theoretical results are applied to resolve a class of mean-variance portfolio selection problems.We provide corresponding numerical simulation results and economic explanations.展开更多
This paper attempts to study two-person nonzero-sum games for denumerable continuous-time Markov chains determined by transition rates,with an expected average criterion.The transition rates are allowed to be unbounde...This paper attempts to study two-person nonzero-sum games for denumerable continuous-time Markov chains determined by transition rates,with an expected average criterion.The transition rates are allowed to be unbounded,and the payoff functions may be unbounded from above and from below.We give suitable conditions under which the existence of a Nash equilibrium is ensured.More precisely,using the socalled "vanishing discount" approach,a Nash equilibrium for the average criterion is obtained as a limit point of a sequence of equilibrium strategies for the discounted criterion as the discount factors tend to zero.Our results are illustrated with a birth-and-death game.展开更多
This paper presents a novel optimal synchronization control method for multi-agent systems with input saturation.The multi-agent game theory is introduced to transform the optimal synchronization control problem into ...This paper presents a novel optimal synchronization control method for multi-agent systems with input saturation.The multi-agent game theory is introduced to transform the optimal synchronization control problem into a multi-agent nonzero-sum game.Then,the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman(HJB)equations with nonquadratic input energy terms.A novel off-policy reinforcement learning method is presented to obtain the Nash equilibrium solution without the system models,and the critic neural networks(NNs)and actor NNs are introduced to implement the presented method.Theoretical analysis is provided,which shows that the iterative control laws converge to the Nash equilibrium.Simulation results show the good performance of the presented method.展开更多
The existence and uniqueness of the solutions for one kind of forward-backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions.Th...The existence and uniqueness of the solutions for one kind of forward-backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions.Then these results were applied to nonzero-sum differential games with random jumps to get the explicit form of the open-loop Nash equilibrium point by the solution of the forward-backward stochastic differential equations.展开更多
The existence and uniqueness of the solutions for one kind of forward- backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions. ...The existence and uniqueness of the solutions for one kind of forward- backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions. Then these results were applied to nonzero-sum differential games with random jumps to get the explicit form of the open-loop Nash equilibrium point by the solution of the forward-backward stochastic differential equations.展开更多
When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game ...When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.展开更多
In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft g...In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft gives rise to a dynamic and real-time game,complicated further by the presence of perturbation.The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system.To overcome this challenge,we introduce the model prediction and iterative correction technique proposed in model predictive static programming,enabling the generation of strategies in analytical iterative form for nonlinear systems.Subsequently,we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation,tailored to address the practical complexities of leader–follower pursuit-evasion scenarios.Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.展开更多
基金supported by the National Natural Science Foundation of China(62433014,62373287,62573324,62333005,62273255)in part by the International Exchange Program for Graduate Students of Tongji University(4360143306)+3 种基金in part by the Fundamental Research Funds for Central Universities(22120230311)supported by DeutscheForschungsgemeinschaft(DFG,German Research Foundation)under Germany’s Excellence Strategy(EXC 2075390740016,468094890)support by the Stuttgart Center for Simulation Science(SimTech)the International Max Planck Research School for Intelligent Systems(IMPRS-IS)for supporting Y.Xie。
文摘Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.
基金Supported by the National Natural Science Foundation of China(No.61101223)
文摘To keep the secrecy performance from being badly influenced by untrusted relay(UR), a multi-UR network through amplify-and-forward(AF) cooperative scheme is put forward, which takes relay weight and harmful factor into account. A nonzero-sum game is established to capture the interaction among URs and detection strategies. Secrecy capacity is investigated as game payoff to indicate the untrusted behaviors of the relays. The maximum probabilities of the behaviors of relay and the optimal system detection strategy can be obtained by using the proposed algorithm.
基金supported in part by the National Natural Science Foundation of China(62173051)the Fundamental Research Funds for the Central Universities(2024CDJCGJ012,2023CDJXY-010)+1 种基金the Chongqing Technology Innovation and Application Development Special Key Project(CSTB2022TIADCUX0015,CSTB2022TIAD-KPX0162)the China Postdoctoral Science Foundation(2024M763865)
文摘Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.
文摘In a first for the African continent,Senegal will host the Dakar 2026 Youth Olympic Games(YOG)from 31 October to 13 November.The Dakar 2026 YOG carry a strong symbolic ambition,embodied by their motto“Africa welcomes,Dakar celebrates.”Host Senegal sees the event as a catalyst for its influence,the modernisation of its infrastructure,and the mobilisation of its youth.
基金supported by a grant from the Korea Creative Content Agency,funded by the Ministry of Culture,Sports and Tourism of the Republic of Korea in 2025,for the project,“Development of AI-based large-scale automatic game verification technology to improve game production verification efficiency for small and medium-sized game companies”(RS 2024-00393500).
文摘GameQualityAssurance(QA)currently relies heavily onmanual testing,a process that is both costly and time-consuming.Traditional script-and log-based automation tools are limited in their ability to detect unpredictable visual bugs,especially those that are context-dependent or graphical in nature.As a result,many issues go unnoticed during manual QA,which reduces overall game quality,degrades the user experience,and creates inefficiencies throughout the development cycle.This study proposes two approaches to address these challenges.The first leverages a Large Language Model(LLM)to directly analyze gameplay videos,detect visual bugs,and automatically generate QA reports in natural language.The second approach introduces a pipeline method:first generating textual descriptions of visual bugs in game videos using the ClipCap model,then using those descriptions as input for the LLM to synthesize QA reports.Through these two multi-faceted approaches,this study evaluates the feasibility of automated game QA systems.To implement this system,we constructed a visual bug database derived from real-world game cases and fine-tuned the ClipCap model for the game video domain.Our proposed approach aims to enhance both efficiency and quality in game development by reducing the burden of manual QA while improving the accuracy of visual bug detection and ensuring consistent,reliable report generation.
基金supported by the National Key R&D Pro-gram of China:Gravitational Wave Detection Project(Nos.2021YFC2026,2021YFC2202601,2021YFC2202603)the National Natural Science Foundation of China(Nos.12172288 and 12472046)。
文摘The problem of maneuvering for a servicing spacecraft(inspector)to inspect a noncooperative spacecraft(evader)in cislunar space is investigated in this paper.The evader,which may be a malfunctioning or uncontrolled satellite,introduces uncertainties due to its potential maneuvering capabilities.To address this challenge,the scenario is modeled as a special orbital game,incorporating the unique complexities of the cislunar environment.A variable-duration,turn-based inspection and anti-inspection game model is designed.The model defines both players'rules,constraints,and victory conditions,providing a framework for non-cooperative inspection.Strategies for both players are developed and validated based on their dynamical properties.The inspector's strategy integrates two-body Lambert transfers with shooting methods,while the evader's strategy aims to maximize the inspector's fuel consumption.Simulation results show that the evader's optimal strategy involves deliberate fluctuations in its lunar periapsis altitude,with the inspector's requiredΔV up to eight times greater than the evader's.The impact of game constraints is evaluated,and the effectiveness of deploying the inspector in low lunar orbit is compared with the inspector at the Earth-Moon Lagrange point L1.The strengths and weaknesses of both are shown.These findings provide valuable insights for future orbital servicing and orbital games.
基金Supported by the National Program on Key Basic Research Project(2020YFA0713600)the National Natural Science Foundation of China(62272214)。
文摘In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task execution delay and node energy consumption,and the scheduling and adaptation challenges brought about by device heterogeneity,urgently need to be addressed.To tackle this problem,this paper constructs a multi-objective real-time task scheduling model that considers task real-time performance,execution delay,system energy consumption,and node interests.The model aims to minimize the delay upper bound and total energy consumption while maximizing system satisfaction.A real-time task scheduling algorithm based on bilateral matching game is proposed.By designing a bidirectional preference mechanism between tasks and computing nodes,combined with a multi-round stable matching strategy,accurate matching between tasks and nodes is achieved.Simulation results show that compared with the baseline scheme,the proposed algorithm significantly reduces the total execution cost,effectively balances the task execution delay and the energy consumption of compute nodes,and takes into account the interests of each network compute node.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12571549,12571592,12471463,12022113,12101573)。
文摘Vaccination is a key strategy to curb the spread of epidemics.Heterologous vaccination,unlike homologous vaccination which acts on a single target and forms a single immune barrier,covers multiple targets for broader protection.Yet,heterologous vaccination involves a complex decision process that conventional game-theoretic approaches,such as classical,evolutionary,and minority games cannot adequately capture.The parallel minority game(PMG)can handle bounded-rational,multi-choice decisions,but its application in vaccine research remains rare.In this study,we propose a vaccination-transmission coupled dynamic mechanism based on the parallel minority game and simulate it on a two-dimensional lattice.Using actual observational data and a mean-field mathematical model,we verify the effectiveness of this mechanism in simulating realistic vaccination behavior and transmission dynamics.We further analyze the impact of key parameters,such as vaccine efficacy differences and the proportion of individuals eligible for vaccine switching,on containment effectiveness.Our results demonstrate that heterologous vaccination surpasses homologous vaccination in containment effectiveness,particularly when vaccine efficacy varies significantly.This work provides a novel framework and empirical evidence for understanding individual decision-making and population-wide immunity formation in multi-vaccine settings.
基金supported in part by the National Natural Science Foundation of China(62373022,U2241217,62141604)Beijing Natural Science Foundation(4252043,JQ23019)+4 种基金the Fundamental Research Funds for the Central Universities(JKF-2025037448805,JKF-2025086098295)the Aeronautical Science Fund(2023Z034051001)the Academic Excellence Foundation of BUAA for Ph.D. Studentsthe Science and Technology Innovation2030—Key Project of New Generation Artificial Intelligence(2020AAA0108200)the National Key Research and Development Program of China(2022YFB3305600)。
文摘An attack-resilient distributed Nash equilibrium(NE) seeking problem is addressed for noncooperative games of networked systems under malicious cyber-attacks,i.e.,false data injection(FDI) attacks.Different from many existing distributed NE seeking works,it is practical and challenging to get resilient adaptively distributed NE seeking under unknown and unbounded FDI attacks.An attack-resilient NE seeking algorithm that is distributed(i.e.,independent of global information on the graph's algebraic connectivity,Lipschitz and monotone constants of pseudo-gradients,or number of players),is presented by means of incorporating the consensus-based gradient play with a distributed attack identifier so as to achieve simultaneous NE seeking and attack identification asymptotically.Another key characteristic is that FDI attacks are allowed to be unknown and unbounded.By exploiting nonsmooth analysis and stability theory,the global asymptotic convergence of the developed algorithm to the NE is ensured.Moreover,we extend this design to further consider the attack-resilient NE seeking of double-integrator players.Lastly,numerical simulation and practical experiment results are presented to validate the developed algorithms' effectiveness.
基金supported by Science and Technology Project of SGCC(Research on Distributed Cooperative Control of Virtual Power Plants Based on Hybrid Game)(5700-202418337A-2-1-ZX).
文摘This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint programming approach is adopted to address uncertainties stemming from renewable generation and load demand within individual VPPs,while robust optimization techniques manage electricity and thermal price volatilities.Building upon this foundation,a hierarchical Nash-Stackelberg game model is established across multiple VPPs.Within each VPP,a Stackelberg game resolves the strategic interaction between the operator and photovoltaic prosumers(PVP).Among VPPs,a cooperative Nash bargaining model coordinates alliance formation.The problem is decomposed into two subproblems:maximizing coalitional benefits,and allocating cooperative surpluses via payment bargaining,solved distributively using the alternating direction method of multipliers(ADMM).Case studies demonstrate that the proposed strategy significantly enhances the economic efficiency and uncertainty resilience of multi-VPP alliances.
基金The Natural Science Foundation of Heilongjiang Province(No.LH2023E011)Open Fund of National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment in Changsha University of Science and Technology(No.kfj230105).
文摘To uncover the decision-making mechanisms and evolutionary dynamics of multiple stakeholders in highway noise pollution control,a three-party evolutionary game model involving the government,operators,and the public is constructed.The operation period is divided into different stages for differentiated analysis.A simulation analysis was performed on the Lituo sinking section of the Beijing-Hong Kong-Macao Highway to assess the impact of variations in critical elements on the system.The results indicate that the Lituo sinking section of the Beijing-Hong Kong-Macao Highway is currently in its early stage of development,with the corresponding strategies being active regulation,excessive emissions,and supervision.When the cost of the government’s active regulation decreases from 1×10^(5) to 5×10^(4) yuan,the system converges more rapidly toward the active regulation strategy.When the cost of the operator’s excessive emissions increases from 14.08×10^(6) to 20.00×10^(6) yuan,the system drives the operator toward the standardized emission strategy.In addition,when the cost of public supervision decreases from 15×10^(4) to 5×10^(4) yuan and the compensation paid by operators to the public increases from 1.288×10^(6) to 2.576×10^(6) yuan,the system converges more quickly toward the supervision strategy.The cost of the operator’s excessive emissions serves as the core decision variable for achieving the ideal equilibrium in the three-party game involving government active regulation,operator standardized emissions,and public supervision.
基金supported by the National Natural Science Foundation of China(61702528,61806212,62173336)。
文摘In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dynamic fighting scenarios,and exists situations where the scenario and rule of the Colonel Blotto(CB)game are too restrictive in real world.To address these issues,a support stage is added as supplementary for pre-allocated results,in which a novel two-stage competitive resource assignment problem is formulated based on CB game and stochastic Lanchester equation(SLE).Further,the force attrition in these two stages is formulated as a stochastic progress to consider the complex fighting progress,including the case that the player with fewer resources defeats the player with more resources and wins the battlefield.For solving this two-stage resource assignment problem,nested solving and no-regret learning are proposed to search the optimal resource assignment strategies.Numerical experiments are taken to analyze the effectiveness of the proposed model and study the assignment strategies in various cases.
基金supported by the National Key Research and Development Program of China(2023YFA1009200)the National Natural Science Foundation of China(12401583,12571482,12521001)+2 种基金the Taishan Scholars Climbing Program of Shandong(TSPD20210302)the Basic Research Program of Jiangsu(BK20240416)the General Program of Philosophy and Social Science Research(PSSR)of Shandong Higher Education Institutions(2024ZSMS007)。
文摘This paper studies an indefinite mean-field game with Markov jump parameters,where all agents'diffusion terms depend on control variables and both state and control average terms(x.^((N)),u.^((N)))are considered.One notable aspect is the relaxation of the assumption regarding the positivity or non-negativity of weight matrices within costs,allowing for zero or even negative values.By virtue of mean-field methods and decomposition techniques,we have derived decentralized strategies presented by Hamiltonian systems and a new type of consistency condition system.These systems consist of fully coupled regime-switching forward-backward stochastic differential equations that do not conform to the Monotonicity condition.The well-posedness of these strategies is established by employing a relaxed compensator method with an easily verifiable Condition(RC)and the decomposition technique.Furthermore,we demonstrate that the resulting decentralized strategies achieve anϵ-Nash equilibrium in the indefinite case without any assumptions on admissible control sets using novel estimates of the disturbed state and cost function.Finally,our theoretical results are applied to resolve a class of mean-variance portfolio selection problems.We provide corresponding numerical simulation results and economic explanations.
基金supported by National Science Foundation for Distinguished Young Scholars of China (Grant No. 10925107)Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2011)
文摘This paper attempts to study two-person nonzero-sum games for denumerable continuous-time Markov chains determined by transition rates,with an expected average criterion.The transition rates are allowed to be unbounded,and the payoff functions may be unbounded from above and from below.We give suitable conditions under which the existence of a Nash equilibrium is ensured.More precisely,using the socalled "vanishing discount" approach,a Nash equilibrium for the average criterion is obtained as a limit point of a sequence of equilibrium strategies for the discounted criterion as the discount factors tend to zero.Our results are illustrated with a birth-and-death game.
基金Project supported by the National Key R&D Program of China(No.2018YFB1702300)the National Natural Science Foundation of China(Nos.61722312 and 61533017)。
文摘This paper presents a novel optimal synchronization control method for multi-agent systems with input saturation.The multi-agent game theory is introduced to transform the optimal synchronization control problem into a multi-agent nonzero-sum game.Then,the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman(HJB)equations with nonquadratic input energy terms.A novel off-policy reinforcement learning method is presented to obtain the Nash equilibrium solution without the system models,and the critic neural networks(NNs)and actor NNs are introduced to implement the presented method.Theoretical analysis is provided,which shows that the iterative control laws converge to the Nash equilibrium.Simulation results show the good performance of the presented method.
基金Project supported by the National Natural Science Foundation of China (No.10371067) thePlanned Item for the Outstanding Young Teachers of Ministry of Education of China (No.2057) the Special Fund for Ph.D. Program of Ministry of Education of China ( No.20020422020) and the Fok Ying Tung Education Foundation for Young College Teachers(No.91064)
文摘The existence and uniqueness of the solutions for one kind of forward-backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions.Then these results were applied to nonzero-sum differential games with random jumps to get the explicit form of the open-loop Nash equilibrium point by the solution of the forward-backward stochastic differential equations.
基金国家自然科学基金，Outstanding Young Teachers of Ministry of Education of China，Special Fund for Ph.D.Program of Ministry of Education of China，Fok Ying Tung Education Foundation
文摘The existence and uniqueness of the solutions for one kind of forward- backward stochastic differential equations with Brownian motion and Poisson process as the noise source were given under the monotone conditions. Then these results were applied to nonzero-sum differential games with random jumps to get the explicit form of the open-loop Nash equilibrium point by the solution of the forward-backward stochastic differential equations.
基金National Natural Science Foundation of China(NSFC61773142,NSFC62303136)。
文摘When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.
基金supported,in part,by the National Natural Science Foundation of China(Nos.12372050 and 62088101)the Zhejiang Provincial Natural Science Foundation of China(No.LR20F030003).
文摘In this paper,we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information.In the proposed problem,the interplay between two spacecraft gives rise to a dynamic and real-time game,complicated further by the presence of perturbation.The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system.To overcome this challenge,we introduce the model prediction and iterative correction technique proposed in model predictive static programming,enabling the generation of strategies in analytical iterative form for nonlinear systems.Subsequently,we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation,tailored to address the practical complexities of leader–follower pursuit-evasion scenarios.Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.
