Manuscript received November 29, 2023; revised December 30, 2023; accepted January 15, 2024; published March 15, 2024
Abstract—This paper provides a comprehensive review of the research on intention analysis and optimal decision-making methods for group games in the field of air combat. Air combat is considered as a complex game process involving multiple participants, stages, and incomplete information. It encompasses three key aspects: intention analysis, mission planning, and autonomous decision-making. The paper presents an overview of the principles, methodologies, and applications related to intention representation and recognition methods, competition and cooperation models, as well as optimal decision generation algorithms in group games. Furthermore, future research directions are proposed including the integration of optimization algorithms with learning algorithms, exploration of large-scale optimization techniques, and investigation into leveraging deep learning approaches for modeling, prediction, and optimization in crowd games.
Keywords—group games, intention analysis, mission planning, autonomous decision-making
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Cite: Zeyu Zhu, "Game Intention Analysis and Optimal Decision Methods: A Survey," International Journal of Engineering and Technology vol. 16, no. 1, pp. 46-51, 2024.
