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Learning Scalable task assignment.with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of Systems Science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing 100081China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV *** the problem into task assignment.and low-level interception strategies is a widely used ***-based approaches for task assignment.are a promising *** studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict *** contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to *** achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment.method for sensor target coverage problem,a scalable centralized assignment.method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is ***,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free ***,the IPCR mechanism is parallelized to enable efficient *** validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various *** experimental results show that the proposed algorithm not only achieves conflict-free task assignment.but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

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