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A New Qualitative Measurement Method of Game Situation Cognitive Uncertainty Based on Deep Learning
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Yongguang WANG1, 2, Jing SUN1, 2, Nan ZHANG1, Xiujian ZHANG1, 2
Missiles and Space Vehicles | 2025, 48(4) : 45 - 52
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Missiles and Space Vehicles | 2025, 48(4): 45-52
• Artificial Intelligence Technology •
A New Qualitative Measurement Method of Game Situation Cognitive Uncertainty Based on Deep Learning
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Yongguang WANG1, 2, Jing SUN1, 2, Nan ZHANG1, Xiujian ZHANG1, 2
Affiliations
  • 1. Beijing Aerospace Institute for Metrology and Measurement Technology, Beijing, 100076
  • 2. Key Laboratory of Artificial Intelligence Measurement and Standards for State Market Regulation, Beijing, 100076
Published: 2025-08-25 doi: 10.7654/j.issn.2097-1974.20250406
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At present, with the complex and changeable game environment, deep learning models such as deep convolutional neural networks are introduced to assist in improving personnel's cognition and decision-making level of the game situation. However, when deep learning is introduced into game situation understanding, it also introduces data uncertainty and cognitive uncertainty in artificial intelligence, which leads to problems such as divergence of artificial intelligence prediction results. Key elements of uncertainty in the measurement process of game situation understanding are decomposed, extracted and measurement modeling constructed based on the measurement uncertainty evaluation method. The experimental results show that the physical measurement method based on GUM can effectively measure and evaluate the cognitive uncertainty of game situation accurately and efficiently. Finally, based on Monte Carlo method, the proposed new qualitative measurement method of game situation cognition uncertainty is verified, which shows the accuracy and applicability of the proposed method.

deep learning  /  situation understanding  /  cognitive uncertainty  /  measurement uncertainty  /  Monte Carlo method
Yongguang WANG, Jing SUN, Nan ZHANG, Xiujian ZHANG. A New Qualitative Measurement Method of Game Situation Cognitive Uncertainty Based on Deep Learning[J]. Missiles and Space Vehicles, 2025 , 48 (4) : 45 -52 . DOI: 10.7654/j.issn.2097-1974.20250406
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Year 2025 volume 48 Issue 4
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Article Info
doi: 10.7654/j.issn.2097-1974.20250406
  • Receive Date：2024-10-10
  • Online Date：2025-10-27
  • Published：2025-08-25
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History
  • Received：2024-10-10
  • Revised：2025-07-13
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Affiliations
    1. Beijing Aerospace Institute for Metrology and Measurement Technology, Beijing, 100076
    2. Key Laboratory of Artificial Intelligence Measurement and Standards for State Market Regulation, Beijing, 100076
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