Research onManeuver Decision-Making ofMulti-Agent Adversarial Game in a Random Interference Environment
作者机构：Equipment Management and UAV Engineering College Air Force Engineering University Xi'an 710051 China National Key Laboratory of Unmanned Aerial Vehicle Technology Xi'an 710051 China College of Information Technology Nanjing Police University Nanjing 210023 China
出 版 物：《Computers, Materials and Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2024年第81卷第1期
页 面：1879-1903页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Behavior decision-making maneuver multi-agent nonlinear mathematical modeling stochastic evolutionary game
摘 要：The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances. This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment. It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players, as well as the impact of participants manipulative behaviors on the state changes of the players. A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario. Subsequently, the strategy selection interaction relationship, strategy evolution stability, and dynamic decision-making process of the game players are investigated and verified by simulation experiments. The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent s strategies. Especially in a highly uncertain environment, even small information asymmetry or miscalculation may have a significant impact on decision-making. This also confirms the feasibility and effectiveness of the method proposed in the paper, which can better explain the behavioral decision-making process of the agent in the interaction process. This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model. © 2024 The Authors. Published by Tech Science Press.
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