Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.

Discreet investors exert greater influence on cooperation in the public goods game

This paper studies the evolutionary process of cooperative behavior in a public goods game model with heterogeneous investment strategies in square lattices.In the proposed model,players are divided into defectors,cooperators and discreet investors.Among these,defectors do not participate in investing,discreet investors make heterogeneous investments based on the investment behavior and cooperation value of their neighbors,and cooperators invest equally in each neighbor.In real life,heterogeneous investment is often accompanied by time or economic costs.The discreet investors in this paper pay a certain price to obtain their neighbors'investment behavior and cooperation value,which quantifies the time and economic costs of the heterogeneous investment process.The results of Monte Carlo simulation experiments in this study show that discreet investors can effectively resist the invasion of the defectors,form a stable cooperative group and expand the cooperative advantage in evolution.However,when discreet investors pay too high a price,they lose their strategic advantage.The results in this paper help us understand the role of heterogeneous investment in promoting and maintaining human social cooperation.

Effect of distribution of fines on evolution of cooperation in spatial public goods game

In the realm of public goods game,punishment,as a potent tool,stands out for fostering cooperation.While it effectively addresses the first-order free-rider problem,the associated costs can be substantial.Punishers incur expenses in imposing sanctions,while defectors face fines.Unfortunately,these monetary elements seemingly vanish into thin air,representing a loss to the system itself.However,by virtue of the redistribution of fines to cooperators and punishers,not only can we mitigate this loss,but the rewards for these cooperative individuals can be enhanced.Based upon this premise,this paper introduces a fine distribution mechanism to the traditional pool punishment model.Under identical parameter settings,by conducting a comparative experiment with the conventional punishment model,the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game.The experimental results clearly demonstrate that,in instances where the punishment cost is prohibitively high,the cooperative strategies of the traditional pool punishment model may completely collapse.However,the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies,thus highlighting its effectiveness in promoting and preserving cooperation,even in the face of substantial punishment cost.

Cooperative maneuver decision making for multi-UAV air combat based on incomplete information dynamic game

Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.

How to promote cooperative innovation in environmentally friendly technology:a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China.First,we constructed an evolutionary game model comprising the factors of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies.Using MATLAB simulation,we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’willingness to cooperate.Results showed that when the values of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies exceeded the threshold,innovators’willingness to cooperate was significantly enhanced.Furthermore,the proportion of innovators who cooperated with others gradually increased to 100%;otherwise,it gradually decreased to 0%.Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China,we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation,low income from cooperative innovation,weak profitability of innovators,and weak market constraints.

Cooperative game theory-based steering law design of a CMG system

Spacecraft require a large-angle manoeuvre when performing agile manoeuvring tasks, therefore a control moment gyroscope(CMG) is employed to provide a strong moment.However, the control of the CMG system easily falls into singularity, which renders the actuator unable to output the required moment. To solve the singularity problem of CMGs, the control law design of a CMG system based on a cooperative game is proposed. First, the cooperative game model is constructed according to the quadratic programming problem, and the cooperative strategy is constructed. When the strategy falls into singularity, the weighting coefficient is introduced to carry out the strategy game to achieve the optimal strategy. In theory, it is proven that the cooperative game manipulation law of the CMG system converges, the sum of the CMG frame angular velocities is minimized, the energy consumption is small, and there is no output torque error. Then, the CMG group system is simulated.When the CMG system is near the singular point, it can quickly escape the singularity. When the CMG system falls into the singularity, it can also escape the singularity. Considering the optimization of angular momentum and energy consumption, the feasibility of the CMG system steering law based on a cooperative game is proven.

A cooperative detection game:UAV swarm vs.one fast intruder

This paper studies a special defense game using unmanned aerial vehicle(UAV)swarm against a fast intruder.The fast intruder applies an offensive strategy based on the artificial potential field method and Apollonius circle to scout a certain destination.As defenders,the UAVs are arranged into three layers:the forward layer,the midfield layer and the back layer.The co-defense mechanism,including the role derivation method of UAV swarm and a guidance law based on the co-defense front point,is introduced for UAV swarm to co-detect the intruder.Besides,five formations are designed for comparative analysis when ten UAVs are applied.Through Monte Carlo experiments and ablation experiment,the effectiveness of the proposed co-defense method has been verified.

Cooperative Game Analysis of Tourism Enterprise Coupling from the Perspective of Industrial Eco-Network

Based on the introduction of the connotations and characteristics of tourism industrial eco-network,it has expatiated on the connotations of and approaches to enterprise coupling in tourism industrial eco-network.As there are different understandings and definitions of these connotations,the following four aspects must be achieved in order to realize coupling in the real sense for the enterprises in the network.① Establish the idea of "the whole is larger than the sum of all the parts",and construct interests community of tourism industrial eco-network.② Construct cooperation mechanism of joint struggle to transfer the advantages of the single to the advantages of the whole.③ Create and maintain strong service culture.④ Avoid as many service blunders as possible and construct damage warning mechanism in industrial eco-network.With the construction of the game model of tourism enterprise coupling and corresponding analysis,the results indicate that the mode of loose cooperation between enterprises in the tourism industry could hardly reach any forceful binding agreements.Consequently it is hard to realize the coordinated effects brought about by the cooperative game of tourism enterprise coupling and these enterprises would often come to a "prisoner dilemma" because of present tiny benefits.In the end,it suggests that during the process of competition tourism enterprises should also strengthen mutual cooperation as relying upon the platform of industrial eco-network.

Modelling of a Human Driver’s Interaction with Vehicle Automated Steering Using Cooperative Game Theory

The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.

Cooperative and Competitive Multi-Agent Systems:From Optimization to Games

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.

Cooperative driving model for non-signalized intersections with cooperative games

Cooperative driving around intersections has aroused increasing interest in the last five years.Meanwhile,driving safety in non-signalized intersections has become an issue that has attracted attention globally.In view of the potential collision risk when more than three vehicles approach a non-signalized intersection from different directions,we propose a driving model using cooperative game theory.First,the characteristic functions of this model are primarily established on each vehicle’s profit function and include safety,rapidity and comfort indicators.Second,the Shapley theorem is adopted,and its group rationality,individual rationality,and uniqueness are proved to be suitable for the characteristic functions of the model.Following this,different drivers’characteristics are considered.In order to simplify the calculation process,a zero-mean normalization method is introduced.In addition,a genetic algorithm method is adopted to search an optimal strategy set in the constrained multi-objective optimization problem.Finally,the model is confirmed as valid after simulation with a series of initial conditions.

Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform(CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization,user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

Profit Allocation Scheme Among Players in Supply-Chain Based on Shapley Value of Fuzzy Bi-cooperative Games

The Shapley value of fuzzy bi-eooperative game is developed based on the conventional Shapley value of bi-cooperative game. From the viewpoint that the players can participate in the coalitions to a certain extent and there are at least two independent cooperative projects for every player to choose, Shapley value which is introduced by Grabisch is extended to the case of fuzzy bi-cooperative game by Choquet integral. Moreover, the explicit fuzzy Shapley value is given. The explicit fuzzy Shapley function can be used to allocate the profits among players in supply-chain under the competitive and uncertain environment.

A NOVEL COOPERATIVE SPECTRUM SENSING METHOD BASED ON COOPERATIVE GAME THEORY

A novel cooperative sensing method is proposed in this paper. The proposed scheme adopts sensing creditability degree to characterize the impact of the distance and the channel parameters on the sensing result,and considers that each user has different average SNR and different decision threshold,by using General Nash Bargaining Solution (GNBS) strategy in Cooperative Game Theory (CGT),the detection performance for two-user case are derived. For multi-user case,the sensing performance is obtained with Hungarian method. Compared with the traditional schemes such as Nash Bargaining Solution (NBS) and AND,the proposed scheme covers all the factors mentioned above,and enhances the sensing rationality and reliability. Simulation results show that the proposed scheme can further improve the sensing performance and creditability.

Shapley Value for Cooperative Games with Fuzzy Coalition

Fuzzy Shapley values are developed based on conventional Shapley value. This kind of fuzzy cooperative games admit the representation of rates of players＇ participation to each coalition. And they can be applicable to both supperadditive and subadditvie cooperative games while other kinds of fuzzy cooperative games can only be superadditive. An explicit form of the Shapley function on fuzzy games with λ-fuzzy measure was also proposed.

Cooperative Differential Game for Model Energy-Bandwidth Efficiency Tradeoff in the Internet of Things

Internet of Things （IoT） refers to an infrastructure which enables the forms of com- munication and collaboration between people and things, and between things themselves. In order to improve its performance, we present a tradeoff between bandwidth and energy con- sumption in the loT in this paper. A service providing model is built to find the relation- ship between bandwidth and energy consump- tion using a cooperative differential game mo- del. The game solution is gotten in the condi- tion of grand coalition, feedback Nash equili- brium and intermediate coalitions and an allo- cation policy is obtain by Shapley theory. The results are shown as follows. Firstly, the per- formance of IoT decreases with the increasing of bandwidth cost or with the decreasing of en- ergy cost; secondly, all the nodes in the IoT com- posing a grand coalition can save bandwidth and energy consumption; thirdly, when the fac- tors of bandwidth cost and energy cost are eq- ual, the obtained number of provided services is an optimised value which is the trade-off between energy and bandwidth consumption.

Broadband ＆ Digital Content-Couple Subscriber Cooperative Relaying Networks for Uplink Transmission using Hierarchical Game Approach

Cooperation allows wireless network users to benefit from various gains such as an in- crease in the achieved rate or an improvement in the bit error rate. In the paper, we propose a distributed Hierarchical Game （HG） theoretic framework over multi-user cooperative communication networks to stimulate cooperation and improve the network performance. First, we study a two- user decision making game in the OFDMA based subscriber cooperative relaying network, in which subscribers transmit their own data in the first phase, while helping to retransmit their partner＇s or choosing to freeride in the second phase. Instead of consulting to a global optimal solution, we decouple the cooperation resource allocation into two level subproblems： a user level Nash game for distributed cooperation decision and a Base Station （BS） level coalition game for centralized resource allocation. In the proposed HG algorithm, where mutual cooperation is preferred and total payoff is transferable, we prove it converges to a unique optimal equilibrium and resolve the subcarrier as-signment and power allocation among the couples. Besides, we discuss the existence of the publishing and rewarding coefficients in order to encourage cooperation. Then, we extend the HG to multi-user cases by coupling among subscribers according to the location information. The simulation results show that the proposed scheme with the distributed HG game achieves a well tradeoff between fairness and efficiency by improving the transmission efficiency of adverse users and outperforms those employing centralized schemes.

Game theoretic analysis for pricing-based incentive mechanism in non-dedicated cooperative relay networks

In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node(ICN) forwards data through participating cooperation node(PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations(CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN's metric measured by bit-per-Joule and increase the PCN's revenue.

Bargaining Game Theoretic Power Control in Selfish Cooperative Relay Networks

Wireless cooperative communications require appropriate power allocation （PA） between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate （SER） at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution （NBS） to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.

Cooperative Game Approach for Scheduling in Two-Virtual-Antenna Cellular Networks with Relay Stations Fairness Consideration

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.