Capability Construction of C4ISR Based on AI Planning

被引:6
|
作者
Jiao, Zhiqiang [1 ]
Yao, Peiyang [2 ]
Zhang, Jieyong [2 ]
Wan, Lujun [3 ]
Wang, Xun [1 ]
机构
[1] Air Force Engn Univ, Grad Coll, Xian 710077, Shaanxi, Peoples R China
[2] Air Force Engn Univ, Informat & Nav Coll, Xian 710077, Shaanxi, Peoples R China
[3] Air Force Engn Univ, ACT Nav, Xian 710077, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial intelligence planning; C4ISR; capability construction; service-oriented architecture; FF; SEARCH; SYSTEM;
D O I
10.1109/ACCESS.2019.2902043
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers a capability construction problem of the C4ISR system under service- oriented architecture. A capability construction model is first established and described in the planning domain definition language as an artificial intelligence (AI) planning problem. To adapt the complex requirements of a C4ISR system and large scale of required services, an incremental macro-operation learning method based on n-gram analysis is proposed, and an enhanced domain is generated using a relaxation scheme. To improve the efficiency of the search algorithm, an ordered-hill-climbing (OHC) method is designed based on the length of the operations. With the above procedures, the AI planner, using macro-operation and the OHC, is presented for capability construction problems. The simulation results show that this method can effectively shorten the search time of capability construction.
引用
收藏
页码:31997 / 32008
页数:12
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