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On future combat autonomous decision technology for starcraft
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Science & Technology Review | 2021, 39(5) : 117 - 125
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Science & Technology Review | 2021, 39(5): 117-125
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On future combat autonomous decision technology for starcraft
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HUANG Bincheng1,2, CHEN Si1,2, GAO Fang1,2, GE Jianjun1,2, WU Xueling3
Affiliations
    1. Key Laboratory of Cognition and Intelligence Technology, China Electronics Technology Group Corporation, Beijing 100086, China;
    2. Information Science Academy, China Electronics Technology Group Corporation, Beijing 100086, China;
    3. CNGC North Automatic Control Technology Institute, Taiyuan 030006, China
Published: 2021-03-13 doi: 10.3981/j.issn.1000-7857.2021.05.013
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StarCraft is an important game for studying the future combat autonomous decision technology. Similarities between StarCraft and the autonomous decision process are described. Planning, learning, and uncertainty in decision-making algorithms for StarCraft are also analyzed. Firstly, the key problem of future combat autonomous decision-making technology is discussed in terms of decision complexity. Then, the article proposes to create a large-scale war game to clarify the development of future battle autonomous decision-making technologies, such as system's top-level architecture, game AI modeling technology, large game engines, etc. in order to provide a useful reference for the development of autonomous decision system intelligent technology.
intelligent operation  /  real time strategic games  /  swarm intelligence  /  autonomous strategy  /  simulation game  /  winning mechanism  /  artificial intelligence
HUANG Bincheng, CHEN Si, GAO Fang, GE Jianjun, WU Xueling. On future combat autonomous decision technology for starcraft[J]. Science & Technology Review, 2021 , 39 (5) : 117 -125 . DOI: 10.3981/j.issn.1000-7857.2021.05.013
Year 2021 volume 39 Issue 5
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doi: 10.3981/j.issn.1000-7857.2021.05.013
  • Receive Date:2020-04-27
  • Online Date:2021-04-23
  • Published:2021-03-13
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  • Received:2020-04-27
  • Revised:2020-11-03
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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