Attack-defense differential game to strength allocation strategies generation

Lingwei Li, Bing Xiao, Shihong Su, Haichao Zhang, Xiwei Wu, Yiming Guo

Research output: Contribution to journalArticlepeer-review

Abstract

This paper addresses a difficult problem of strength allocation strategies generation with various adversaries and complex factors. Firstly, to investigate the strength allocation strategies generation problem, an attack-defense differential game problem is formulated based on an improved Lanchester equation. Secondly, a numerical method, multi-intervals simultaneous orthogonal collocation decomposition (MISOCD) method, is proposed to obtain the strength allocation strategies from the constructed model. Compared with the analytical method, MISOCD does not need to derive the necessary conditions. Thirdly, this study designs an approximated solution generation strategy based on adaptive learning pigeon-inspired optimization algorithm to pregenerate the approximated strength allocation strategies in order to solve the initial value sensitivity problem. The approximated strategies are then used as the initial value guess of MISOCD method to generate optimal strength allocation strategies. Finally, two attack-defense numerical simulations verify the effectiveness of strength allocation strategies generated by the proposed approach. Our proposed results provide a theoretical guide for both making attack-defense strength allocation strategies and assessing confrontation actions.

Original languageEnglish
Pages (from-to)3219-3236
Number of pages18
JournalOptimal Control Applications and Methods
Volume44
Issue number6
DOIs
StatePublished - 1 Nov 2023

Keywords

  • complicated attack-defense process
  • differential game
  • numerical method
  • simultaneous orthogonal collocation decomposition
  • strength allocation strategies

Fingerprint

Dive into the research topics of 'Attack-defense differential game to strength allocation strategies generation'. Together they form a unique fingerprint.

Cite this