Research on Mission Assignment Assurance of Remote Rocket Barrage Based on Stackelberg Game

Ya-bin, Wang; Cheng, Zhonghua; Liu, Lijia; Zhu, Dunxiang; Zhao, Rudong

doi:10.1088/1757-899x/493/1/012056

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“…Task assignment changes the weapon target assignment (WTA) fire unit-target model to a task-target assignment model. This improves the ability to coordinate the various components, and the assignment scheme is more flexible, providing fundamental assurance of maximum operational effectiveness ( Wang et al, 2019 ). With the continuous adoption of new technologies on both sides of the battlefield, the combat process is becoming increasingly complex, involving many elements.…”

Section: Introductionmentioning

confidence: 99%

Intelligent air defense task assignment based on hierarchical reinforcement learning

et al. 2022

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Modern air defense battlefield situations are complex and varied, requiring high-speed computing capabilities and real-time situational processing for task assignment. Current methods struggle to balance the quality and speed of assignment strategies. This paper proposes a hierarchical reinforcement learning architecture for ground-to-air confrontation (HRL-GC) and an algorithm combining model predictive control with proximal policy optimization (MPC-PPO), which effectively combines the advantages of centralized and distributed approaches. To improve training efficiency while ensuring the quality of the final decision. In a large-scale area air defense scenario, this paper validates the effectiveness and superiority of the HRL-GC architecture and MPC-PPO algorithm, proving that the method can meet the needs of large-scale air defense task assignment in terms of quality and speed.

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Section: Introductionmentioning

confidence: 99%