首页> 外国专利> The design of PBC mode Priority tabel of Recovery Agent simulation based on Reinforcement Learning

The design of PBC mode Priority tabel of Recovery Agent simulation based on Reinforcement Learning

机译:基于强化学习的恢复剂仿真PBC模式优先表的设计

摘要

The present invention relates to a damage recovery agent and a method that can be applied in the “simulation-based organizational unit emergency training technology simulation” to which reinforcement learning is applied. It relates to the damage recovery agent applied with the AI control level for designing and implementing the organizational unit emergency preparedness training technology” system and its method. To this end, the emergency recovery agent management tool uses AI through reinforcement learning in the simulation situation linked to the military situation in preparation for excessive time delays and errors of the model operator when designing a simulation-based emergency training technology development project for damage recovery. It is characterized by proposing a damage recovery agent system that adjusts/controls the damage recovery agent so that the automatic damage recovery simulation is performed by the priority algorithm of the PBC (perceived behavior control) mode.
机译:损伤回收剂及其方法技术领域本发明涉及损伤回收剂和可以应用于应用增强学习的“基于模拟的组织单元紧急训练技术模拟”中的方法。它涉及损伤回收剂,用于设计和实施组织单位应急准备培训技术“系统及其方法的AI控制水平。为此,紧急恢复代理管理工具通过增强学习,在仿真情况下,与军事局势相关联的仿真情况,以准备模型运营商的过度时间延迟和误差在设计基于模拟的紧急训练技术开发项目中的损伤恢复时。其特征在于提出调整/控制损坏回收剂的损伤回收剂系统,使得通过PBC(感知行为控制)模式的优先级算法来执行自动损坏恢复模拟。

著录项

  • 公开/公告号KR20210042577A

    专利类型

  • 公开/公告日2021-04-20

    原文格式PDF

  • 申请/专利权人 (주) 심네트;

    申请/专利号KR1020190125300

  • 发明设计人 이승용;오명섭;이상만;

    申请日2019-10-10

  • 分类号G09B9;G06N20;

  • 国家 KR

  • 入库时间 2022-08-24 18:26:57

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