Study on group air to ground attack-defends hierarchical dynamic decision-making

Li, Zhang; An, Zhang; Yong-fang, Zhang; Zhi-fu, Shi

doi:10.1016/s1004-4132(07)60126-1

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…This three-tier architecture based on mobile edge computing brings computing and storage resources closer to offshore devices and sensors, enabling lower latency and faster responses. This architecture can also reduce the dependence on remote cloud computing resources, reduce the DT latency and network congestion, and improve the system reliability [122]. At the same time, this architecture exhibits the good flexibility and scalability needed to adapt to the needs of MIoT applications of different sizes and complexities [123].…”

Section: Mobile Edge Computing (Mec)mentioning

confidence: 99%

A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges

Liu,

Zhu,

Huang

et al. 2023

JMSE

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Future generation communication systems are exemplified by 5G and 6G wireless technologies, and the utilization of integrated air-to-sea (A2S) communication infrastructure is employed to extend network coverage and enhance data throughput to support data-driven maritime applications. These ground-breaking techniques have promoted the rapid development of the maritime internet of things (MIoT). In particular, the integration of air base stations (ABSs) in the MIoT can achieve broadband, low-delay, and reliable wireless transmissions. Considering the potential of ABS-enabled communications, this survey presents the state of the art in the A2S integrated MIoT. More specifically, relevant A2S integrated MIoT architectures are discussed together with the role of their building blocks. Next, we introduce the enabling technologies, including the sensor, communication, data processing and storage, and security and privacy protection techniques. Then, resource allocation, cloud/edge computing and caching, routing protocols, and spatial location optimization in the maritime environment are discussed and grouped based on their performance targets. Additionally, we also show the potential applications of the A2S integrated MIoT in marine environment monitoring, traffic, navigation safety, and resources management. Finally, several future challenges in the area of the A2S integrated MIoT are given, related to the technical security, reliability, and energy efficiency, etc.

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Section: Mobile Edge Computing (Mec)mentioning

confidence: 99%

A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges

Liu,

Zhu,

Huang

et al. 2023

JMSE

View full text Add to dashboard Cite

show abstract

“…A divide and conquer approach is a solution to address this type of problems including obstacle avoidance [34]. Inspired by the idea of hierarchical decision-making, this work decomposes the source task into several sub-tasks [35]. For a source obstacle avoidance task, the prior experience of the trained sub-tasks is assembled to form an ensemble policy, which guides the agent to select an action for this complicated task.…”

Section: The Training Algorithm For Each Sub-taskmentioning

confidence: 99%

An Experience Aggregative Reinforcement Learning With Multi-Attribute Decision-Making for Obstacle Avoidance of Wheeled Mobile Robot

Ning

Meng

et al. 2020

IEEE Access

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A variety of reinforcement learning (RL) methods are developed to achieve the motion control for the robotic systems, which has been a hot issue. However, the performance of the conventional RL methods often encounters a bottleneck, because the robots have difficulty in choosing an appropriate action in the control task due to the exploration-exploitation dilemma. To address this problem and improve the learning performance, this work introduces an experience aggregative reinforcement learning method with a Multi-Attribute Decision-Making (MADM) to achieve the real-time obstacle avoidance of wheeled mobile robot (WMR). The proposed method employs an experience aggregation method to cluster experiential samples and it can achieve more effective experience storage. Moreover, to achieve the effective action selection using the prior experience, an action selection policy based on a Multi-Attribute Decision-Making is proposed. Inspired by the hierarchical decision-making, this work decomposes the original obstacle avoidance task into two sub-tasks using a divide-and-conquer approach. Each sub-task is trained individually by a double Q-learning using a simple reward function. Each sub-task learns an action policy, which enables the sub-task to selects an appropriate action to achieve a single goal. The standardized rewards of sub-tasks are calculated when fusing these sub-tasks to eliminate differences in rewards for sub-tasks. Then, the proposed method integrates the prior experience of three trained sub-tasks via an action policy based on a MADM to complete the source task. Simulation results show that the proposed method outperforms competitors.

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“…(1) Economic benefits Enterprises pursue profit maximization. In general, production profit is the difference between total income (the product of price and output) and total cost [5]. Coal prices are subject to large fluctuations in the market.…”

Section: Objective Functionmentioning

confidence: 99%

Coal Mining Strategy of Energy Saving and Emission Reduction Based on Multi-objective Planning

Feng¹

2019

Proceedings of the 2019 4th International Conference on Modern Management, Education Technology and Social Science (MMETSS 2019

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This paper considers the three objectives which are coal production, ecological environment and energy consumption. In order to meet the constraints of project investment funds, the mining capacity constraints, the total amount of resources in the mining area, the mutual restraint between the various processes, and the related energy in the "13th Five-Year Plan". Under the common constraints of consumption and pollution emission standards, a static model for energy conservation and emission reduction in coal mining areas based on multi-objective optimization was constructed. The model is solved by designing the algorithm, and the model is applied to the case of Hongyan Coal Mine in Junlian County. The validity, scientificity and rationality of the model and algorithm are verified.

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Study on group air to ground attack-defends hierarchical dynamic decision-making

Cited by 7 publications

References 2 publications

A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges

A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges

An Experience Aggregative Reinforcement Learning With Multi-Attribute Decision-Making for Obstacle Avoidance of Wheeled Mobile Robot

Coal Mining Strategy of Energy Saving and Emission Reduction Based on Multi-objective Planning

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