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1. 发明申请

US20160321563A1 OPTIMIZED ARTIFICIAL INTELLIGENCE MACHINES THAT ALLOCATE PATROL AGENTS TO MINIMIZE OPPORTUNISTIC CRIME BASED ON LEARNED MODEL 审中-公开
标题翻译：优化人工智能机器，根据学习型号最小化机会性犯罪分配PATROL代理
公开(公告)号：US20160321563A1
公开(公告)日：2016-11-03
申请号：US15144184
申请日：2016-05-02
申请人： Arunesh Sinha , Milind Tambe , Chao Zhang
发明人： Arunesh Sinha , Milind Tambe , Chao Zhang
IPC分类号： G06N99/00 , G06Q50/26
CPC分类号： G06N20/00 , G06N3/008 , G06N7/005 , G06Q50/26
摘要： An optimized artificial intelligence machine may: receive information indicative of the times, locations, and types of crimes that were committed over a period of time in a geographic area; receive information indicative of the number and locations of patrol agents that were patrolling during the period of time; build a learning model based on the received information that learns the relationships between the locations of the patrol agents and the crimes that were committed; and determine whether and where criminals would commit new crimes based on the learning model and a different number of patrol agents or locations of patrol agents. The optimized artificial intelligence machine may determine an optimum location of a pre-determined number of patrolling agents to minimize the number or seriousness of crimes in a geographic area based on the learned model of the relationships between the locations of the patrol agents and the crimes that were committed, and may automatically activate or position one or more of the patrolling agents in accordance with the determination.
摘要翻译：优化的人造智能机器可以：接收指示在一段时间内在地理区域中犯下的犯罪的次数，位置和类型的信息; 收到指示在该段期间巡逻的巡逻人员的人数和地点的资料; 根据收到的信息，建立学习模式，了解巡逻人员的位置与所犯罪行之间的关系; 并根据学习模式和不同数量的巡逻人员或巡逻人员的地点确定犯罪分子是否以及在哪里犯新的罪行。优化的人造智能机器可以基于学习的巡逻人员的位置和犯罪的位置之间的关系的模型来确定预定数量的巡逻者的最佳位置，以最小化地理区域中的犯罪的数量或严重性并且可以根据确定自动激活或定位一个或多个巡逻代理。

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