Capability Construction of C4ISR Based on AI Planning

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Abstract

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.

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Jiao, Z., Yao, P., Zhang, J., Wan, L., & Wang, X. (2019). Capability Construction of C4ISR Based on AI Planning. IEEE Access, 7, 31997–32008. https://doi.org/10.1109/ACCESS.2019.2902043

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