A game-theoretic approach for federated learning:A trade-off among privacy,accuracy and energy

Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become possible.Distributed devices not only provide adequate training data,but also cause privacy leakage and energy consumption.How to optimize the energy consumption in distributed communication systems,while ensuring the privacy of users and model accuracy,has become an urgent challenge.In this paper,we define the FL as a 3-layer architecture including users,agents and server.In order to find a balance among model training accuracy,privacy-preserving effect,and energy consumption,we design the training process of FL as game models.We use an extensive game tree to analyze the key elements that influence the players’decisions in the single game,and then find the incentive mechanism that meet the social norms through the repeated game.The experimental results show that the Nash equilibrium we obtained satisfies the laws of reality,and the proposed incentive mechanism can also promote users to submit high-quality data in FL.Following the multiple rounds of play,the incentive mechanism can help all players find the optimal strategies for energy,privacy,and accuracy of FL in distributed communication systems.

Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players usually move in three-dimensional space with a three-degree-of-freedom control. In this paper,we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game, in which the pursuer follows a three-degree-of-freedom control, and the evader moves freely. First, we describe the pursuer's three-degree-of-freedom control and the evader's relative coordinate. We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs(HJBI) method, which divides the pursuit-evasion process into the navigation and acceleration phases. Besides, we analyze the maximum allowable speed for the pursuer to capture the evader successfully and provide the strategy with which the evader can escape when the pursuer's speed exceeds the threshold. We further conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.

Problematic Use of Video Games in Schools in Northern Benin (2023)

Objective: To study the problematic use of video games among secondary school students in the city of Parakou in 2023. Methods: Descriptive cross-sectional study conducted in the commune of Parakou from December 2022 to July 2023. The study population consisted of students regularly enrolled in public and private secondary schools in the city of Parakou for the 2022-2023 academic year. A two-stage non-proportional stratified sampling technique combined with simple random sampling was adopted. The Problem Video Game Playing (PVP) scale was used to assess problem gambling in the study population, while anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS). Results: A total of 1030 students were included. The mean age of the pupils surveyed was 15.06 ± 2.68 years, with extremes of 10 and 28 years. The [13 - 18] age group was the most represented, with a proportion of 59.6% (614) in the general population. Females predominated, at 52.8% (544), with a sex ratio of 0.89. The prevalence of problematic video game use was 24.9%, measured using the Video Game Playing scale. Associated factors were male gender (p = 0.005), pocket money under 10,000 cfa (p = 0.001) and between 20,000 - 90,000 cfa (p = 0.030), addictive family behavior (p < 0.001), monogamous family (p = 0.023), good relationship with father (p = 0.020), organization of video game competitions (p = 0.001) and definite anxiety (p Conclusion: Substance-free addiction is struggling to attract the attention it deserves, as it did in its infancy everywhere else. This study complements existing data and serves as a reminder of the need to focus on this group of addictions, whose problematic use of video games remains the most frequent due to its accessibility and social tolerance. Preventive action combined with curative measures remains the most effective means of combating the problem at national level.

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.

A Value for Games Defined on Graphs

Given a graph g=( V,A ) , we define a space of subgraphs M with the binary operation of union and the unique decomposition property into blocks. This space allows us to discuss a notion of minimal subgraphs (minimal coalitions) that are of interest for the game. Additionally, a partition of the game is defined in terms of the gain of each block, and subsequently, a solution to the game is defined based on distributing to each player (node and edge) present in each block a payment proportional to their contribution to the coalition.

A Blockchain-Based Game Approach to Multi-Microgrid Energy Dispatch

As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,traceability and tamper-proof features,is an importantway to achieve efficient consumption andmulti-party supply of new energy.In this article,we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’revenue,consider the degree of microgrid users’preference for electricity thus increasing users’reliance on the blockchainmarket,and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue.The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.

Evolutionary game dynamics of combining two different aspiration-driven update rules in structured populations

In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.

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.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete Information

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the learning process and adapt their policies sequentially.Our method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based frameworks.Furthermore,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control laws.The efficacy of our method is illustrated by three examples.

The Triple Helix of innovation as a double game involving domestic and foreign actors

Purpose:The collaboration relationships between innovation actors at a geographic level may be considered as grouping two separate layers,the domestic and the foreign.At the level of each layer,the relationships and the actors involved constitute a Triple Helix game.The paper distinguished three levels of analysis:the global grouping together all actors,the domestic grouping together domestic actors,and the foreign related to only actors from partner countries.Design/methodology/approach:Bibliographic records data from the Web of Science for South Korea and West Africa breakdown per innovation actors and distinguishing domestic and international collaboration are analyzed with game theory.The core,the Shapley value,and the nucleolus are computed at the three levels to measure the synergy between actors.Findings:The synergy operates more in South Korea than in West Africa;the government is more present in West Africa than in South Korea;domestic actors create more synergy in South Korea,but foreign more in West Africa;South Korea can consume all the foreign synergy,which is not the case of West Africa.Research limitations:Research data are limited to publication records;techniques and methods used may be extended to other research outputs.Practical implications:West African governments should increase their investment in science,technology,and innovation to benefit more from the synergy their innovation actors contributed at the foreign level.However,the results of the current study may not be sufficient to prove that greater investment will yield benefits from foreign synergies.Originality/value:This paper uses game theory to assess innovation systems by computing the contribution of foreign actors to knowledge production at an area level.It proposes an indicator to this end.

Impacts of Human Activities and Season on Species Diversity and Abundance of Butterflies in Mpanga Kipengere Game Reserve and Surrounding Farmlands, Tanzania

Maintaining natural habitats is crucial for the preservation of insects and other species that indicate environmental changes. However, the Mpanga/Kipengere Game Reserve and its surrounding farmlands are facing disturbance due to human activities, which is putting many wildlife species, particularly larger mammals, at risk. To determine the impact of human activities on butterfly species diversity and abundance in the reserve and its surrounding areas, we conducted a study from November 2021 to October 2023. We collected butterfly data using transect walks and baited traps in two habitat types. Our study yielded 2799 butterfly Individuals ranging in 124 species divided into five families habitat, season, and anthropogenic factors are significant environmental variables influencing species diversity and abundance of butterflies. Therefore, it’s important to protect habitat and dry-season water for the conservation of invertebrates such as butterflies. Our study findings provide essential information for ecological monitoring and future assessment of the Mpanga/Kipengere Game Reserve ecosystem health.

A Mean-Field Game for a Forward-Backward Stochastic System With Partial Observation and Common Noise

This paper considers a linear-quadratic(LQ) meanfield game governed by a forward-backward stochastic system with partial observation and common noise,where a coupling structure enters state equations,cost functionals and observation equations.Firstly,to reduce the complexity of solving the meanfield game,a limiting control problem is introduced.By virtue of the decomposition approach,an admissible control set is proposed.Applying a filter technique and dimensional-expansion technique,a decentralized control strategy and a consistency condition system are derived,and the related solvability is also addressed.Secondly,we discuss an approximate Nash equilibrium property of the decentralized control strategy.Finally,we work out a financial problem with some numerical simulations.

A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

Malicious attacks against data are unavoidable in the interconnected,open and shared Energy Internet(EI),Intrusion tolerant techniques are critical to the data security of EI.Existing intrusion tolerant techniques suffered from problems such as low adaptability,policy lag,and difficulty in determining the degree of tolerance.To address these issues,we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas:(1)it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights;and (2)it combines a tournament competition model with incentive weights to obtain optimal strategies for each stage of the game process.Extensive experiments are conducted in the IEEE 39-bus system,whose results demonstrate the feasibility of the incentive weights,confirm the proposed strategy strengthens the system’s ability to tolerate aggression,and improves the dynamic adaptability and response efficiency of the aggression-tolerant system in the case of limited resources.

Game Theory Based Model for Predictive Analytics Using Distributed Position Function

This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.

Distributed Optimal Variational GNE Seeking in Merely Monotone Games

In this paper, the optimal variational generalized Nash equilibrium(v-GNE) seeking problem in merely monotone games with linearly coupled cost functions is investigated, in which the feasible strategy domain of each agent is coupled through an affine constraint. A distributed algorithm based on the hybrid steepest descent method is first proposed to seek the optimal v-GNE. Then, an accelerated algorithm with relaxation is proposed and analyzed, which has the potential to further improve the convergence speed to the optimal v-GNE. Some sufficient conditions in both algorithms are obtained to ensure the global convergence towards the optimal v-GNE. To illustrate the performance of the algorithms, numerical simulation is conducted based on a networked Nash-Cournot game with bounded market capacities.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage.To solve the problem of the interests of different subjects in the operation of the energy storage power stations(ESS)and the integrated energy multi-microgrid alliance(IEMA),this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game.In the upper layer,ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.In the lower layer,IEMA optimizes the output of various energy conversion coupled devices within the IEMA,as well as energy interaction and demand response(DR),based on the energy interaction prices provided by ESS.The results demonstrate that the optimization strategy proposed in this paper not only effectively balances the benefits of the IEMA and ESS but also enhances energy consumption rates and reduces IEMA energy costs.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Mongolian Traditional Game-“Shagai”Features of Mongolian Traditional Games

In today’s interconnected global society,a crucial aspect that defines the identity of an independent country is its distinctive national heritage and values.Every country has many different cultures,and children’s games exist in every culture.Every culture has unique characteristics and norms that have been agreed upon by the members of the culture(Usman&Yusuf,2022).Mongolians believe that the future of their nation can be discerned through the toys that children play with.These toys reflect Mongolia’s nomadic culture,rich heritage,customs,precious belongings,and unique playthings.Mongolian culture and mentality are nurtured in children through play,and an essential aspect of Mongolian games is their close association with people’s work and way of life.The Mongolian toys stand as a significant intellectual contribution of the Mongolian people to human history.