J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2020 , Vol. 25 >Issue 5: 561 - 568

DOI: https://doi.org/10.1007/s12204-020-2226-8

Missile-Target Situation Assessment Model Based on Reinforcement Learning

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  • (Department of Automation; Key Laboratory of System Control and Information Processing of Ministry of Education;
    Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education,
    Shanghai Jiao Tong University, Shanghai 200240, China)

Online published: 2020-09-11

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Abstract

In situation assessment (SA) of missile versus target fighter, the traditional SA models generally
have the characteristics of strong subjectivity and poor dynamic adaptability. This paper considers SA as an
expectation of future returns and establishes a missile-target simulation battle model. The actor-critic (AC)
algorithm in reinforcement learning (RL) is used to train the evaluation network, and a missile-target SA model
is established in simulation battle training. Simulation and comparative experiments show that the model can
effectively estimate the expected effect of missile attack under the current situation, and it provides an effective
basis for missile attack decision.

Key words： situation assessment (SA); battle model; reinforcement learning (RL); actor-critic (AC) algorithm

Cite this article

ZHANG Yun, Lü Runyan, CAI Yunze . Missile-Target Situation Assessment Model Based on Reinforcement Learning[J]. Journal of Shanghai Jiaotong University(Science), 2020 , 25(5) : 561 -568 . DOI: 10.1007/s12204-020-2226-8

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