Journal of System Simulation ›› 2021, Vol. 33 ›› Issue (10): 2344-2355.doi: 10.16182/j.issn1004731x.joss.20-0551

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Research on CGF-oriented Intention Recognition Behavioral Modeling Framework

Xu Kai, Zeng Yunxiu, Wu Wansen, Yin Quanjun, Zha Yabing   

  1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
  • Received:2020-07-31 Revised:2020-09-21 Online:2021-10-18 Published:2021-10-18

Abstract: As an important cognitive behavior in Computer Generated Forces (CGF), Intention Recognition reasons the temporal relations between actions of friends and enemies to recognize their true intentions, and provides the observer with far more focused decision-making ability. In order to further formalize the modeling of CGF-oriented intention recognition, the paper reviews the worldwide research development from 1980s, along with the designs and implementations of different methods. Following the theory of Situation Awareness, the paper analyzes the situation awareness process of CGF, its impacting factors and constraints and proposes a generalized intention recognition framework considering different problem characteristics, constraints and basic recognition process. The framework could be the theoretical guidance to the modeling of CGF intention recognition that satisfying different application demands.

Key words: computer generated forces, cognitive behavioral modeling, intention recognition, situation awareness

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