The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Lin...The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Linguistic variables can be represented with degrees of truthfulness and falsehood by using fuzzy logic. Like other artificial intelligence techniques, the fuzzy logic is used in many different areas. In computer game industry, it can be used to develop artificial intelligence based games. In this paper, the author discusses about usage of the fuzzy logic technique in computer games and developed a basic game based on the fuzzy logic. In this game, a computer controlled character can behave differently according to changing situations.展开更多
A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the coopera...A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the cooperative operation problem of multi-PHIES connected to the same ADN is studied.A low-carbon hybrid game coordination strategy for multi-PHIES accessing ADN based on dynamic carbon base price is proposed in the paper.Firstly,multi-PHIES are constructed to form a PHIES alliance,including a hydrogen-doped gas turbine(HGT),hydrogen-doped gas boiler(HGB),power to gas and carbon capture system(P2G-CCS),and other equipment.Secondly,a hybrid game system model of the ADN and PHIES alliance is constructed,in which the ADN and PHIES alliance constitute a master-slave game,and the members of the PHIES alliance constitute a cooperative game.An improved Shapley value is proposed to deal with the problem of cost share among members in the alliance.Thirdly,an improved stepped carbon trading based on dynamic carbon baseline price is proposed.Thecarbon emissions at each moment and the total carbon emissions in a cycle are set as the dynamic adjustment factors of the carbon baseline price.The pricing mechanism of carbon baseline price increases with carbon emissions is constructed so that carbon emissions decrease.Finally,the quadratic interpolation optimization(QIO)algorithm is combined with Gurobi to solve the model.The results of the example analysis show that the cost of ADN is reduced by 4.47%,the cost of PHIES 1 is reduced by 3.67%,the cost of PHIES 2 is reduced by 0.97%,and the cost of PHIES 3 is reduced by 4.91%respectively.The total carbon emissions of the PHIES alliance are reduced by 7.08%.The low-carbon and economical operation of the multi-PHIES accessing ADN is achieved.展开更多
This paper investigates the problem of optimal secure control for networked control systems under hybrid attacks.A control strategy based on the Stackelberg game framework is proposed,which differs from conventional m...This paper investigates the problem of optimal secure control for networked control systems under hybrid attacks.A control strategy based on the Stackelberg game framework is proposed,which differs from conventional methods by considering both denial-of-service(DoS)and false data injection(FDI)attacks simultaneously.Additionally,the stability conditions for the system under these hybrid attacks are established.It is technically challenging to design the control strategy by predicting attacker actions based on Stcakelberg game to ensure the system stability under hybrid attacks.Another technical difficulty lies in establishing the conditions for mean-square asymptotic stability due to the complexity of the attack scenarios Finally,simulations on an unstable batch reactor system under hybrid attacks demonstrate the effectiveness of the proposed strategy.展开更多
In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.T...In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.The designed distributed controller consists of two parts:a dynamic average consensus part that asymptotically reproduces the unknown NE,and an adaptive reference-tracking module responsible for steering EL systems’positions to track a desired trajectory.The generalized Barbalat’s Lemma is used to overcome the discontinuity of the closed-loop system caused by the switching networks.The proposed algorithm is illustrated by a sensor network deployment problem.展开更多
The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This r...Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This review synthesizes the theoretical advancements,computational approaches,emerging challenges,and possible research directions in the field.Firstly,we briefly review the fundamental theory of continuous-time optimal control,including Pontryagin's maximum principle(PMP)and dynamic programming principle(DPP).Secondly,we present the foundational results in optimal impulse control,including necessary conditions and sufficient conditions.Thirdly,we systematize impulse game methodologies,from Nash equilibrium existence theory to the connection between Nash equilibrium and systems stability.Fourthly,we summarize the numerical algorithms including the intelligent computation approaches.Finally,we examine the new trends and challenges in theory and applications as well as computational considerations.展开更多
Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduli...Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduling problems and forming the cOrrespOnding agents. Then, the importance and the restriction of each agent are cOnsidered, to obtain an order of simple scheduling problems based on the cooperation game theory. With this order, the scheduling of sub-questions is implemented in term of rules, and the almost optimal scheduling results for meeting the restriction can be obtained. Experimental results verify the effectiveness of the proposed scheduling algorithm.展开更多
After building a dynamic evolutionary game model, the essay studies the stability of the equilibrium in the game between the commercial banks and the closed-loop supply chain(CLSC) enterprises. By design of systematic...After building a dynamic evolutionary game model, the essay studies the stability of the equilibrium in the game between the commercial banks and the closed-loop supply chain(CLSC) enterprises. By design of systematic mechanism based on system dynamics theory, capital chains of independent small and medium-sized enterprises(SMEs) on CLSC are organically linked together. Moreover, a comparative simulation is studied for the previous independent and post-design dependent systems. The study shows that with business expanding and market risk growing, the independent finance chains of SMEs on CLSC often take on a certain vulnerability, while the SMEs closed-loop supply chain finance system itself is with a strong rigidity and concerto.展开更多
Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization.In a multi-agent system...Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization.In a multi-agent system,agents with a certain degree of autonomy generate complex interactions due to the correlation and coordination,which is manifested as cooperative/competitive behavior.This survey focuses on multi-agent cooperative optimization and cooperative/non-cooperative games.Starting from cooperative optimization,the studies on distributed optimization and federated optimization are summarized.The survey mainly focuses on distributed online optimization and its application in privacy protection,and overviews federated optimization from the perspective of privacy protection me-chanisms.Then,cooperative games and non-cooperative games are introduced to expand the cooperative optimization problems from two aspects of minimizing global costs and minimizing individual costs,respectively.Multi-agent cooperative and non-cooperative behaviors are modeled by games from both static and dynamic aspects,according to whether each player can make decisions based on the information of other players.Finally,future directions for cooperative optimization,cooperative/non-cooperative games,and their applications are discussed.展开更多
Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and...Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.展开更多
With the increasing proportion of renewable energy in the power market,the demands on government financial subsidies are gradually increasing.Thus,a joint green certificate-carbon emission right-electricity multi-mark...With the increasing proportion of renewable energy in the power market,the demands on government financial subsidies are gradually increasing.Thus,a joint green certificate-carbon emission right-electricity multi-market trading process is proposed to study the market-based strategy for renewable energy.Considering the commodity characteristics of green certificates and carbon emission rights,the dynamic cost models of green certificates and carbon rights are constructed based on the Rubinstein game and ladder pricing models.Furthermore,considering the irrational bidding behavior of energy suppliers in the actual electricity market,an evolutionary game based multi-market bidding optimization model is presented.Subsequently,it is solved using a composite differential evolutionary algorithm.Finally,the case study results reveal that the proposed model can increase profits and the consumption rate of renewable energy and reduce carbon emission.展开更多
This paper investigates the channel diversity problem in high frequency(HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each use...This paper investigates the channel diversity problem in high frequency(HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each user equipment(UE) has individual communication demand. In order to maximize the communication probability of the whole system, a matching-potential game framework is designed. In detail, the channel diversity problem is decomposed into two sub-problems. One is channel-transmitter matching problem, which can be formulated as a many-to-one matching game. The other is the transmitter allocation problem which decides the transmission object that each transmitter communicates with under channel-transmitter matching result, and this sub-problem can be modeled as a potential game. A multiple round stable matching algorithm(MRSMA) is proposed, which obtains a stable matching result for the first sub-problem, and a distributed BR-based transmitter allocation algorithm(DBRTAA) is designed to reach Nash Equilibrium(NE) of the second sub-problem. Simulation results verify the effectiveness and superiority of the proposed method.展开更多
The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual incom...The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual income and global benefits and build the logical architecture of the multi-agent system. Besides, to verify the feasibility of the method, the cyclic neural network is optimized, the bi-directional coordination network is built as the training network for deep learning, and specific training scenes are simulated as the training background. After a certain number of training iterations, the model can learn simple strategies autonomously. Also,as the training time increases, the complexity of learning strategies rises gradually. Strategies such as obstacle avoidance, firepower distribution and collaborative cover are adopted to demonstrate the achievability of the model. The model is verified to be realizable by the examples of obstacle avoidance, fire distribution and cooperative cover. Under the same resource background, the model exhibits better convergence than other deep learning training networks, and it is not easy to fall into the local endless loop.Furthermore, the ability of the learning strategy is stronger than that of the training model based on rules, which is of great practical values.展开更多
Owing to the fluctuant renewable generation and power demand,the energy surplus or deficit in nanogrids embodies differently across time.To stimulate local renewable energy consumption and minimize long-term energy co...Owing to the fluctuant renewable generation and power demand,the energy surplus or deficit in nanogrids embodies differently across time.To stimulate local renewable energy consumption and minimize long-term energy costs,some issues still remain to be explored:when and how the energy demand and bidirectional trading prices are scheduled considering personal comfort preferences and environmental factors.For this purpose,the demand response and two-way pricing problems concurrently for nanogrids and a public monitoring entity(PME)are studied with exploiting the large potential thermal elastic ability of heating,ventilation and air-conditioning(HVAC)units.Different from nanogrids,in terms of minimizing time-average costs,PME aims to set reasonable prices and optimize profits by trading with nanogrids and the main grid bi-directionally.Such bilevel energy management problem is formulated as a stochastic form in a longterm horizon.Since there are uncertain system parameters,time-coupled queue constraints and the interplay of bilevel decision-making,it is challenging to solve the formulated problems.To this end,we derive a form of relaxation based on Lyapunov optimization technique to make the energy management problem tractable without forecasting the related system parameters.The transaction between nanogrids and PME is captured by a one-leader and multi-follower Stackelberg game framework.Then,theoretical analysis of the existence and uniqueness of Stackelberg equilibrium(SE)is developed based on the proposed game property.Following that,we devise an optimization algorithm to reach the SE with less information exchange.Numerical experiments validate the effectiveness of the proposed approach.展开更多
Aiming at the physical layer security(PLS)secure transmission existing in the information backhaul link of the satellite-UAV integrated(SUI)network,a two-layer Stackelberg game model(TSGM)that can resist full-duplex(F...Aiming at the physical layer security(PLS)secure transmission existing in the information backhaul link of the satellite-UAV integrated(SUI)network,a two-layer Stackelberg game model(TSGM)that can resist full-duplex(FD)eavesdropping and jamming attacks is proposed.The confrontation relationship between the UAV network and the attacker is established as the first layer Stackelberg game.The source UAV adjusts its own transmission power strategy according to the attacker’s jamming strategy to resist malicious jamming attacks.The internal competition and cooperation relationship in UAV network is modeled as the second layer Stackelberg game,and the optimal cooperative UAV transmits jamming signal to the attacker to resist malicious eavesdropping attacks.Aiming at the“selfishness”of UAV nodes,a price incentive mechanism is established to encourage UAV to actively participate in cooperation,so as to maximize the advantages of cooperative communication.For the proposed TSGM,we construct the utility function and analyze the closed equilibrium solution of the game model,and design a three-stage optimal response iterative(TORI)algorithm to solve the game equilibrium.The simulation results show that the proposed TSGM can effectively increase the utility of the source UAV and improve the enthusiasm of cooperation compared with other power control models.展开更多
With increasing reforms related to integrated energy systems(IESs),each energy subsystem,as a participant based on bounded rationality,significantly influences the optimal scheduling of the entire IES through mutual l...With increasing reforms related to integrated energy systems(IESs),each energy subsystem,as a participant based on bounded rationality,significantly influences the optimal scheduling of the entire IES through mutual learning and imitation.A reasonable multiagent joint operation strategy can help this system meet its low-carbon objectives.This paper proposes a bilayer low-carbon optimal operational strategy for an IES based on the Stackelberg master-slave game and multiagent joint operation.The studied IES includes cogeneration,power-to-gas,and carbon capture systems.Based on the Stackelberg master-slave game theory,sellers are used as leaders in the upper layer to set the prices of electricity and heat,while energy producers,energy storage providers,and load aggregators are used as followers in the lower layer to adjust the operational strategy of the system.An IES bilayer optimization model based on the Stackelberg master-slave game was developed.Finally,the Karush-Kuhn-Tucker(KKT)condition and linear relaxation technology are used to convert the bilayer game model to a single layer.CPLEX,which is a mathematical program solver,is used to solve the equilibrium problem and the carbon emission trading cost of the system when the benefits of each subject reach maximum and to analyze the impact of different carbon emission trading prices and growth rates on the operational strategy of the system.As an experimental demonstration,we simulated an IES coupled with an IEEE 39-node electrical grid system,a six-node heat network system,and a six-node gas network system.The simulation results confirm the effectiveness and feasibility of the proposed model.展开更多
A non-cooperative game model based on brittleness entropy is formulated for preventing cascading failure of complex systems.Subsystems of a complex system are mapped to the players of the game.The influence of collaps...A non-cooperative game model based on brittleness entropy is formulated for preventing cascading failure of complex systems.Subsystems of a complex system are mapped to the players of the game.The influence of collapsed subsystems to other subsystems is also taken into account in the definition of payoff function except for their own entropy increase.This influence is named brittleness entropy.Each player has two optional strategies;rational for negative entropy and irrational for negative entropy.The model is designed to identify the players who select an irrational strategy for negative entropy.The players who select the irrational strategy for negative entropy continue to compete for negative entropy after the recovery of ordered state and make other subsystems can' t get enough negative entropy to reduce entropy increase.It leads to cascading failure of the complex system in the end.Genetic algorithm is used to seek the solution of game model,and the simulation result verifies the effectiveness of the proposed model.The model provides a new way to prevent cascading failure of complex systems.展开更多
It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption,relative position and interaction comprehensively.Therefore,the load distributio...It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption,relative position and interaction comprehensively.Therefore,the load distribution strategy based on power consumption and robust adaptive game control is proposed in this paper.The study is on a"2-lead"multi-lift system of four tandem heli-copters carrying a load cooperatively.First,based on the hierarchical control,the load distribution problem is divided into two parts:the calculation of expected cable force and the calculation of the anti-disturbance cable force.Then,aimed at minimizing the maximum equivalent power of heli-copter,an optimization problem is set up to calculate the expected cable force.Specially,the agent power model is trained by BP neural network,the safe distance constraint between helicopters is set to 2.5 rotor diameters to reduce aerodynamic interference,and the helicopters with different perfor-mance can be considered by introducing the equivalent power factor into the objective function.Next,considering the difference and interaction between helicopters,the robust adaptive differen-tial game control is proposed to calculate the anti-disturbance cable force.Particularly,to solve the coupled Hamiltonian equations,an adaptive solving method for value function is proposed,and its stability is proved in the sense of Lyapunov.The simulation results indicate that the proposed load distribution method based on power consumption is applicable to the entire flight trajectory even there are differences between helicopters.The game control can consider interaction between heli-copters,can deal with different objective functions,and has strong robustness and small steady-state error.Based on the entire strategy,the cable force can be reasonably allocated so as to resist disturbance and improve the flight performance of the whole system.展开更多
In the current stage of Chinese forest ownership reform,the central and local governments as well as the forest farmers play different roles with variations in their expected returns.Managing these respective relation...In the current stage of Chinese forest ownership reform,the central and local governments as well as the forest farmers play different roles with variations in their expected returns.Managing these respective relationships between the forestry stakeholders to maximize their benefits while actively engaging each stakeholder in the collective forest ownership reform process has become an important issue.This study uses the game theory methodology to analyze the relationship between the different reform stakeholders and then builds on the forest farmers' participation in the reform model process at the reform movement micro-level.This model calculates the forest products equilibrium marketing sales and the government subsidies provided to the forest farmers,when the forest farmers willingly participate in the reform process.It will provide a reliable basis for formulation of government policies which positively impacts Chinese forestry reform.展开更多
文摘The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Linguistic variables can be represented with degrees of truthfulness and falsehood by using fuzzy logic. Like other artificial intelligence techniques, the fuzzy logic is used in many different areas. In computer game industry, it can be used to develop artificial intelligence based games. In this paper, the author discusses about usage of the fuzzy logic technique in computer games and developed a basic game based on the fuzzy logic. In this game, a computer controlled character can behave differently according to changing situations.
基金supported by the Central Government Guides the Local Science and Technology Development Fund Project(2023ZY0020)Key R&D and Achievement Transformation Project in Inner Mongolia Autonomous Region(2022YFHH0019)+4 种基金the Fundamental Research Funds for Inner Mongolia University of Science and Technology(2022053)Natural Science Foundation of Inner Mongolia Autonomous Region(2022LHQN05002)NationalNatural Science Foundation of China(52067018)Natural Science Foundation of InnerMongoliaAutonomous Region of China(2025MS05052)Control Science and Engineering Quality Improvement and Cultivation Discipline Project in Inner Mongolia University of Science and Technology.
文摘A park hydrogen-doped integrated energy system(PHIES)can maximize energy utilization as a system with multiple supplies.To realize win-win cooperation between the PHIES and active distribution network(ADN),the cooperative operation problem of multi-PHIES connected to the same ADN is studied.A low-carbon hybrid game coordination strategy for multi-PHIES accessing ADN based on dynamic carbon base price is proposed in the paper.Firstly,multi-PHIES are constructed to form a PHIES alliance,including a hydrogen-doped gas turbine(HGT),hydrogen-doped gas boiler(HGB),power to gas and carbon capture system(P2G-CCS),and other equipment.Secondly,a hybrid game system model of the ADN and PHIES alliance is constructed,in which the ADN and PHIES alliance constitute a master-slave game,and the members of the PHIES alliance constitute a cooperative game.An improved Shapley value is proposed to deal with the problem of cost share among members in the alliance.Thirdly,an improved stepped carbon trading based on dynamic carbon baseline price is proposed.Thecarbon emissions at each moment and the total carbon emissions in a cycle are set as the dynamic adjustment factors of the carbon baseline price.The pricing mechanism of carbon baseline price increases with carbon emissions is constructed so that carbon emissions decrease.Finally,the quadratic interpolation optimization(QIO)algorithm is combined with Gurobi to solve the model.The results of the example analysis show that the cost of ADN is reduced by 4.47%,the cost of PHIES 1 is reduced by 3.67%,the cost of PHIES 2 is reduced by 0.97%,and the cost of PHIES 3 is reduced by 4.91%respectively.The total carbon emissions of the PHIES alliance are reduced by 7.08%.The low-carbon and economical operation of the multi-PHIES accessing ADN is achieved.
基金supported in part by Shanghai Rising-Star Program,China under grant 22QA1409400in part by National Natural Science Foundation of China under grant 62473287 and 62088101in part by Shanghai Municipal Science and Technology Major Project under grant 2021SHZDZX0100.
文摘This paper investigates the problem of optimal secure control for networked control systems under hybrid attacks.A control strategy based on the Stackelberg game framework is proposed,which differs from conventional methods by considering both denial-of-service(DoS)and false data injection(FDI)attacks simultaneously.Additionally,the stability conditions for the system under these hybrid attacks are established.It is technically challenging to design the control strategy by predicting attacker actions based on Stcakelberg game to ensure the system stability under hybrid attacks.Another technical difficulty lies in establishing the conditions for mean-square asymptotic stability due to the complexity of the attack scenarios Finally,simulations on an unstable batch reactor system under hybrid attacks demonstrate the effectiveness of the proposed strategy.
基金supported by the Research Grants Council of the Hong Kong Special Administration Region under the Grant No.14201621。
文摘In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.The designed distributed controller consists of two parts:a dynamic average consensus part that asymptotically reproduces the unknown NE,and an adaptive reference-tracking module responsible for steering EL systems’positions to track a desired trajectory.The generalized Barbalat’s Lemma is used to overcome the discontinuity of the closed-loop system caused by the switching networks.The proposed algorithm is illustrated by a sensor network deployment problem.
基金funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
文摘Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This review synthesizes the theoretical advancements,computational approaches,emerging challenges,and possible research directions in the field.Firstly,we briefly review the fundamental theory of continuous-time optimal control,including Pontryagin's maximum principle(PMP)and dynamic programming principle(DPP).Secondly,we present the foundational results in optimal impulse control,including necessary conditions and sufficient conditions.Thirdly,we systematize impulse game methodologies,from Nash equilibrium existence theory to the connection between Nash equilibrium and systems stability.Fourthly,we summarize the numerical algorithms including the intelligent computation approaches.Finally,we examine the new trends and challenges in theory and applications as well as computational considerations.
文摘Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduling problems and forming the cOrrespOnding agents. Then, the importance and the restriction of each agent are cOnsidered, to obtain an order of simple scheduling problems based on the cooperation game theory. With this order, the scheduling of sub-questions is implemented in term of rules, and the almost optimal scheduling results for meeting the restriction can be obtained. Experimental results verify the effectiveness of the proposed scheduling algorithm.
基金the Natural Science Research Fund of Hubei Province(No.2014BDH121)
文摘After building a dynamic evolutionary game model, the essay studies the stability of the equilibrium in the game between the commercial banks and the closed-loop supply chain(CLSC) enterprises. By design of systematic mechanism based on system dynamics theory, capital chains of independent small and medium-sized enterprises(SMEs) on CLSC are organically linked together. Moreover, a comparative simulation is studied for the previous independent and post-design dependent systems. The study shows that with business expanding and market risk growing, the independent finance chains of SMEs on CLSC often take on a certain vulnerability, while the SMEs closed-loop supply chain finance system itself is with a strong rigidity and concerto.
基金supported in part by the National Natural Science Foundation of China(Basic Science Center Program:61988101)the Sino-German Center for Research Promotion(M-0066)+2 种基金the International(Regional)Cooperation and Exchange Project(61720106008)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)(B17017)the Program of Shanghai Academic Research Leader(20XD1401300).
文摘Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization.In a multi-agent system,agents with a certain degree of autonomy generate complex interactions due to the correlation and coordination,which is manifested as cooperative/competitive behavior.This survey focuses on multi-agent cooperative optimization and cooperative/non-cooperative games.Starting from cooperative optimization,the studies on distributed optimization and federated optimization are summarized.The survey mainly focuses on distributed online optimization and its application in privacy protection,and overviews federated optimization from the perspective of privacy protection me-chanisms.Then,cooperative games and non-cooperative games are introduced to expand the cooperative optimization problems from two aspects of minimizing global costs and minimizing individual costs,respectively.Multi-agent cooperative and non-cooperative behaviors are modeled by games from both static and dynamic aspects,according to whether each player can make decisions based on the information of other players.Finally,future directions for cooperative optimization,cooperative/non-cooperative games,and their applications are discussed.
基金This work was supported by National Natural Science Foundation of China （No. 51621065）.
文摘Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.
基金supported by the National Key R&D Program of China(2017YFB0902200).
文摘With the increasing proportion of renewable energy in the power market,the demands on government financial subsidies are gradually increasing.Thus,a joint green certificate-carbon emission right-electricity multi-market trading process is proposed to study the market-based strategy for renewable energy.Considering the commodity characteristics of green certificates and carbon emission rights,the dynamic cost models of green certificates and carbon rights are constructed based on the Rubinstein game and ladder pricing models.Furthermore,considering the irrational bidding behavior of energy suppliers in the actual electricity market,an evolutionary game based multi-market bidding optimization model is presented.Subsequently,it is solved using a composite differential evolutionary algorithm.Finally,the case study results reveal that the proposed model can increase profits and the consumption rate of renewable energy and reduce carbon emission.
基金supported by the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province under Grant No. BK20160034in part by the National Natural Science Foundation of China under Grant No. 61671473 and No. 61631020in part by the Open Research Foundation of Science and Technology on Communication Networks Laboratory
文摘This paper investigates the channel diversity problem in high frequency(HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each user equipment(UE) has individual communication demand. In order to maximize the communication probability of the whole system, a matching-potential game framework is designed. In detail, the channel diversity problem is decomposed into two sub-problems. One is channel-transmitter matching problem, which can be formulated as a many-to-one matching game. The other is the transmitter allocation problem which decides the transmission object that each transmitter communicates with under channel-transmitter matching result, and this sub-problem can be modeled as a potential game. A multiple round stable matching algorithm(MRSMA) is proposed, which obtains a stable matching result for the first sub-problem, and a distributed BR-based transmitter allocation algorithm(DBRTAA) is designed to reach Nash Equilibrium(NE) of the second sub-problem. Simulation results verify the effectiveness and superiority of the proposed method.
基金supported by the National Natural Science Foundation of China(61503407,61806219,61703426,61876189,61703412)the China Postdoctoral Science Foundation(2016 M602996)。
文摘The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual income and global benefits and build the logical architecture of the multi-agent system. Besides, to verify the feasibility of the method, the cyclic neural network is optimized, the bi-directional coordination network is built as the training network for deep learning, and specific training scenes are simulated as the training background. After a certain number of training iterations, the model can learn simple strategies autonomously. Also,as the training time increases, the complexity of learning strategies rises gradually. Strategies such as obstacle avoidance, firepower distribution and collaborative cover are adopted to demonstrate the achievability of the model. The model is verified to be realizable by the examples of obstacle avoidance, fire distribution and cooperative cover. Under the same resource background, the model exhibits better convergence than other deep learning training networks, and it is not easy to fall into the local endless loop.Furthermore, the ability of the learning strategy is stronger than that of the training model based on rules, which is of great practical values.
基金Supported by the National Key Research and Development Program of China(2018YFB1702300)the National Natural Science Foundation of China(61731012)。
文摘Owing to the fluctuant renewable generation and power demand,the energy surplus or deficit in nanogrids embodies differently across time.To stimulate local renewable energy consumption and minimize long-term energy costs,some issues still remain to be explored:when and how the energy demand and bidirectional trading prices are scheduled considering personal comfort preferences and environmental factors.For this purpose,the demand response and two-way pricing problems concurrently for nanogrids and a public monitoring entity(PME)are studied with exploiting the large potential thermal elastic ability of heating,ventilation and air-conditioning(HVAC)units.Different from nanogrids,in terms of minimizing time-average costs,PME aims to set reasonable prices and optimize profits by trading with nanogrids and the main grid bi-directionally.Such bilevel energy management problem is formulated as a stochastic form in a longterm horizon.Since there are uncertain system parameters,time-coupled queue constraints and the interplay of bilevel decision-making,it is challenging to solve the formulated problems.To this end,we derive a form of relaxation based on Lyapunov optimization technique to make the energy management problem tractable without forecasting the related system parameters.The transaction between nanogrids and PME is captured by a one-leader and multi-follower Stackelberg game framework.Then,theoretical analysis of the existence and uniqueness of Stackelberg equilibrium(SE)is developed based on the proposed game property.Following that,we devise an optimization algorithm to reach the SE with less information exchange.Numerical experiments validate the effectiveness of the proposed approach.
基金supported in part by the National Natural Science Foundation of China under Grant 62071485, Grant 61901519, Grant 62001513in part by the Basic Research Project of Jiangsu Province under Grant BK 20192002the Natural Science Foundation of Jiangsu Province under Grant BK20201334, and BK20200579
文摘Aiming at the physical layer security(PLS)secure transmission existing in the information backhaul link of the satellite-UAV integrated(SUI)network,a two-layer Stackelberg game model(TSGM)that can resist full-duplex(FD)eavesdropping and jamming attacks is proposed.The confrontation relationship between the UAV network and the attacker is established as the first layer Stackelberg game.The source UAV adjusts its own transmission power strategy according to the attacker’s jamming strategy to resist malicious jamming attacks.The internal competition and cooperation relationship in UAV network is modeled as the second layer Stackelberg game,and the optimal cooperative UAV transmits jamming signal to the attacker to resist malicious eavesdropping attacks.Aiming at the“selfishness”of UAV nodes,a price incentive mechanism is established to encourage UAV to actively participate in cooperation,so as to maximize the advantages of cooperative communication.For the proposed TSGM,we construct the utility function and analyze the closed equilibrium solution of the game model,and design a three-stage optimal response iterative(TORI)algorithm to solve the game equilibrium.The simulation results show that the proposed TSGM can effectively increase the utility of the source UAV and improve the enthusiasm of cooperation compared with other power control models.
基金supported by the National Natural Science Foundation of China(Grant No.62063016)。
文摘With increasing reforms related to integrated energy systems(IESs),each energy subsystem,as a participant based on bounded rationality,significantly influences the optimal scheduling of the entire IES through mutual learning and imitation.A reasonable multiagent joint operation strategy can help this system meet its low-carbon objectives.This paper proposes a bilayer low-carbon optimal operational strategy for an IES based on the Stackelberg master-slave game and multiagent joint operation.The studied IES includes cogeneration,power-to-gas,and carbon capture systems.Based on the Stackelberg master-slave game theory,sellers are used as leaders in the upper layer to set the prices of electricity and heat,while energy producers,energy storage providers,and load aggregators are used as followers in the lower layer to adjust the operational strategy of the system.An IES bilayer optimization model based on the Stackelberg master-slave game was developed.Finally,the Karush-Kuhn-Tucker(KKT)condition and linear relaxation technology are used to convert the bilayer game model to a single layer.CPLEX,which is a mathematical program solver,is used to solve the equilibrium problem and the carbon emission trading cost of the system when the benefits of each subject reach maximum and to analyze the impact of different carbon emission trading prices and growth rates on the operational strategy of the system.As an experimental demonstration,we simulated an IES coupled with an IEEE 39-node electrical grid system,a six-node heat network system,and a six-node gas network system.The simulation results confirm the effectiveness and feasibility of the proposed model.
基金Basic Research Foundation from State Administration of Science,Technology and Industry for National Defence,PRC(No.Z192011B001)Science Foundation for Youths of Heilongjiang Province(No.QC2009C87)
文摘A non-cooperative game model based on brittleness entropy is formulated for preventing cascading failure of complex systems.Subsystems of a complex system are mapped to the players of the game.The influence of collapsed subsystems to other subsystems is also taken into account in the definition of payoff function except for their own entropy increase.This influence is named brittleness entropy.Each player has two optional strategies;rational for negative entropy and irrational for negative entropy.The model is designed to identify the players who select an irrational strategy for negative entropy.The players who select the irrational strategy for negative entropy continue to compete for negative entropy after the recovery of ordered state and make other subsystems can' t get enough negative entropy to reduce entropy increase.It leads to cascading failure of the complex system in the end.Genetic algorithm is used to seek the solution of game model,and the simulation result verifies the effectiveness of the proposed model.The model provides a new way to prevent cascading failure of complex systems.
文摘It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption,relative position and interaction comprehensively.Therefore,the load distribution strategy based on power consumption and robust adaptive game control is proposed in this paper.The study is on a"2-lead"multi-lift system of four tandem heli-copters carrying a load cooperatively.First,based on the hierarchical control,the load distribution problem is divided into two parts:the calculation of expected cable force and the calculation of the anti-disturbance cable force.Then,aimed at minimizing the maximum equivalent power of heli-copter,an optimization problem is set up to calculate the expected cable force.Specially,the agent power model is trained by BP neural network,the safe distance constraint between helicopters is set to 2.5 rotor diameters to reduce aerodynamic interference,and the helicopters with different perfor-mance can be considered by introducing the equivalent power factor into the objective function.Next,considering the difference and interaction between helicopters,the robust adaptive differen-tial game control is proposed to calculate the anti-disturbance cable force.Particularly,to solve the coupled Hamiltonian equations,an adaptive solving method for value function is proposed,and its stability is proved in the sense of Lyapunov.The simulation results indicate that the proposed load distribution method based on power consumption is applicable to the entire flight trajectory even there are differences between helicopters.The game control can consider interaction between heli-copters,can deal with different objective functions,and has strong robustness and small steady-state error.Based on the entire strategy,the cable force can be reasonably allocated so as to resist disturbance and improve the flight performance of the whole system.
文摘In the current stage of Chinese forest ownership reform,the central and local governments as well as the forest farmers play different roles with variations in their expected returns.Managing these respective relationships between the forestry stakeholders to maximize their benefits while actively engaging each stakeholder in the collective forest ownership reform process has become an important issue.This study uses the game theory methodology to analyze the relationship between the different reform stakeholders and then builds on the forest farmers' participation in the reform model process at the reform movement micro-level.This model calculates the forest products equilibrium marketing sales and the government subsidies provided to the forest farmers,when the forest farmers willingly participate in the reform process.It will provide a reliable basis for formulation of government policies which positively impacts Chinese forestry reform.
