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game theory-Based IoT Efficient Power Control in Cognitive UAV

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Computers, Materials & Continua 2022年第7期72卷 1561-1578页

作者： Fadhil Mukhlif Norafida Ithnin Omar B.Abdulghafoor Faiz Alotaibi Nourah Saad Alotaibi Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Electronic and Telecommunication Department College of EngineeringThe American University of KurdistanIraq Faculty of Computer Science and Information Technology Universiti Putra MalaysiaSelangorMalaysia Computer Department Faculty of Applied CollegeImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia

With the help of network densification,network coverage as well as the throughput can be improved via ultra-dense networks(UDNs).In tandem,Unmanned Aerial Vehicle(UAV)communications have recently garnered much attention because of their high agility as well as widespread applications.In this paper,a cognitive UAV is proposed for wireless nodes power pertaining to the IoT ground terminal.Further,the UAV is included in the IoT system as the source of power for the wireless nodes as well as for resource allocation.The quality of service(QoS)related to the cognitive node was considered as a utility function based on pricing scheme that was modelled as a non-cooperative game theory in order to maximise users’net utility function.Moreover,an energy efficiency non-cooperative game theory power allocation with pricing scheme(EE-NGPAP)is proposed to obtain an efficient power control within IoT wireless nodes.Further,uniqueness and existence of the Nash equilibrium have been demonstrated mathematically and through simulation.Simulation results show that the proposed energy harvest algorithm demonstrated considerable decrease in transmitted power consumption in terms of average power reduction,which is regarded to be apt with the 5Gnetworks’vision.Finally,the proposed algorithm requires around 4 iterations only to converge to NE which makes the algorithm more suitable in practical heterogeneous scenarios.

关键词： UAV drones WSN IoT game theory energy efficiency 5G&B5G networks

game theory Based Sensor Management in Reducing Target Threat Level Assessment Risk

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 649-659页

作者：庞策单甘霖 Department of Electronic and Optical Engineering Army Engineering University Shijiazhuang CampusShijiazhuang050003China

Sensor management schemes are calculated to reduce target threat level assessment risk in this paper.Hidden Markov model and risk theory are combined to build the target threat level model firstly.Then the target threat level estimation risk is defined.And the sensor management schemes are optimized with the smallest target threat level assessment risk.What’s more,the game theory is applied to calculate the optimal sensor management scheme.Some simulations are conducted to prove that the proposed sensor management method is effective.

关键词： target threat level assessment sensor management hidden Markov model risk theory game theory

game theory, learning, and control systems

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National Science Review 2020年第7期7卷 1118-1119页

作者： Jeff S.Shamma Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology

game theory is the study of interacting decision makers, whereas control systems involve the design of intelligent decision-making devices.When many control systems are interconnected, the result can be viewed through the lens of game theory. This article discusses both long standing connections between these fields as well as new connections stemming from emerging applications.

关键词： game theory

game theory model of exit selection in pedestrian evacuation considering visual range and choice firmness

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Chinese Physics B 2020年第8期29卷 355-362页

作者：王维莉万芳芳卢兆明 Institute of Logistics Science and Engineering Shanghai Maritime UniversityShanghai 201306China Department of Architecture and Civil Engineering City University of Hong KongTat Chee AvenueKowloonHong KongChina

Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much information a pedestrian can perceive,thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit.Besides,the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed.By integrating game theory into a cellular automata simulation framework,the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper.A systematic analysis of the key factors influencing pedestrian evacuation is conducted,including visual radius and choice firmness of a pedestrian,initial crowd distribution of the room,exit layout as well as exit width.It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering,which is adverse to evacuation.The longer the pedestrian's visual radius,the earlier the pedestrian can determine his/her final selection of the exit.Compared with the scenario where the pedestrians are randomly distributed,pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits.Furthermore,the exit layout and exit width also have a certain influence on pedestrian evacuation process.The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.

关键词： game theory exit selection visual range choice firmness

Recognition and interfere deceptive behavior based on inverse reinforcement learning and game theory

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Journal of Systems Engineering and Electronics 2023年第2期34卷 270-288页

作者： ZENG Yunxiu XU Kai College of Systems Engineering National University of Defense TechnologyChangsha 410073China

In real-time strategy(RTS)games,the ability of recognizing other players’goals is important for creating artifical intelligence(AI)players.However,most current goal recognition methods do not take the player’s deceptive behavior into account which often occurs in RTS game scenarios,resulting in poor recognition results.In order to solve this problem,this paper proposes goal recognition for deceptive agent,which is an extended goal recognition method applying the deductive reason method(from general to special)to model the deceptive agent’s behavioral strategy.First of all,the general deceptive behavior model is proposed to abstract features of deception,and then these features are applied to construct a behavior strategy that best matches the deceiver’s historical behavior data by the inverse reinforcement learning(IRL)method.Final,to interfere with the deceptive behavior implementation,we construct a game model to describe the confrontation scenario and the most effective interference measures.

关键词： deceptive path planning inverse reinforcement learning(IRL) game theory goal recognition

Hybrid data-driven framework for shale gas production performance analysis via game theory, machine learning, and optimization approaches

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Petroleum Science 2023年第1期20卷 277-294页

作者： Jin Meng Yu-Jie Zhou Tian-Rui Ye Yi-Tian Xiao Ya-Qiu Lu Ai-Wei Zheng Bang Liang Petroleum Exploration and Production Research Institute SINOPECBeijing100083PR China Jianghan Oilfield Company Research Institute of Exploration and DevelopmentSINOPECWuhan430223HubeiPR China

A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.

关键词： Shale gas Production performance Data-driven Dominant factors game theory Machine learning Derivative-free optimization

Threat sequencing of multiple UCAVs with incomplete information based on game theory

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Journal of Systems Engineering and Electronics 2022年第4期33卷 986-996页

作者： LI Shouyi CHEN Mou WU Qingxian WANG Yuhui College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211100China

The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dynamics of the air combat environment, the weight coefficients of the threat indicators are usually time-varying. Moreover, the air combat data is difficult to be obtained accurately. In this study, a threat sequencing method of multiple UCAVs is proposed based on game theory by considering the incomplete information. Firstly, a zero-sum game model of decision maker( D) and nature(N)with fuzzy payoffs is established to obtain the uncertain parameters which are the weight coefficient parameters of the threat indicators and the interval parameters of the threat matrix. Then,the established zero-sum game with fuzzy payoffs is transformed into a zero-sum game with crisp payoffs(matrix game) to solve. Moreover, a decision rule is addressed for the threat sequencing problem of multiple UCAVs based on the obtained uncertain parameters. Finally, numerical simulation results are presented to show the effectiveness of the proposed approach.

关键词： threat sequencing multiple unmanned combat air vehicles(UCAVs) multi-attribute decision-making(MADM) game theory incomplete information

A Hybrid Music Recommendation Model Based on Personalized Measurement and game theory

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Chinese Journal of Electronics 2023年第6期32卷 1319-1328页

作者： WU Yun LIN Jian MA Yanlong The State Key Laboratory of Public Big Data Guizhou University College of Computer Science and Technology Guizhou University

Music recommendation algorithms, from the perspective of real-time, can be classified into two categories: offline recommendation algorithms and online recommendation algorithms. To improve music recommendation accuracy, especially for the new music(users have no historic listening records on it), and real-time recommendation ability, and solve the interest drift problem simultaneously, we propose a hybrid music recommendation model based on personalized measurement and game theory. This model can be separated into two parts: an offline recommendation part(OFFLRP) and an online recommendation part(ONLRP). In the offline part, we emphasize users personalization. We introduce two metrics named user pursue-novelty degree(UPND) and music popularity(MP) to improve the traditional items-based collaborative filtering algorithm. In the online part, we try to solve the interest drift problem, which is a thorny problem in the offline part. We propose a novel online recommendation algorithm based on game theory. Experiments verify that the hybrid music recommendation model has higher new music recommendation accuracy, decent dynamical personalized recommendation ability, and real-time recommendation capability, and can substantially mitigate the problem of interest drift.

关键词： Music recommendation Personalization game theory Interest drift Hybrid music recommendation model

Water quality characteristics and assessment of Yongding New River by improved comprehensive water quality identification index based on game theory

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Journal of Environmental Sciences 2021年第6期33卷 40-52页

作者： Yu Liu Yucheng Hu Yumei Hu Yuqi Gao Zhenying Liu School of Earth System Science Institute of Surface-Earth System ScienceTianjin UniversityTianjin 300072China Tianjin Hydraulic Science Research Institute Tianjin 300061China School of Mathematics Tianjin UniversityTianjin 300072China School of Environmental Science and Safety Engineering Tianjin University of TechnologyTianjin 300191China

The Yongding New River is essential for the water supplies of Tianjin.To date,there is no comprehensive report that assesses the year-round water quality of the Yongding New River Main stream.Moreover,little attention has been given to determining a combined weight for improving the traditional comprehensive water quality identification index(ICWQII)by the game theory.Seven water quality parameters were investigated monthly along the main stream of the Yongding New River from May 2018 to April 2019.Organic contaminants and nitrogen pollution were mainly caused by point sources pollution,and the total phosphorus mainly by non-point source pollution.Dramatic spatio-temporal variations of water quality parameters were jointly caused by different pollutant sources and hydrometeorological factors.In terms of this study,an improved comprehensive water quality identification index(ICWQII)based on entropy weight or variation coefficient and traditional CWQII underestimated the water qualities,and an ICWQII based on the superstandard multiple method overvalued the assessments.By contrast,water qualities assessments done with an ICWQII based on the game theory matched perfectly with the practical situation.The ICWQII based on game theory proposed in this study takes into account not only the degree of disorder and variation of water quality data,but also the influence of standard-exceeded pollution indicators,whose results are relatively reasonable.All findings and the ICWQII based on game theory can provide scientific support for decisions related to the water environment management of the Yongding New River and other waters.

关键词： Water quality assessment Improved comprehensive water quality identification index game theory Combined weight Spatio-temporal variation Yongding New River