AI-BASED MILITARY DECISION SUPPORT USING NATURAL LANGUAGE

被引:0
|
作者
Moebius, Michael [1 ]
Kallfass, Daniel [1 ]
Doll, Thomas [2 ]
Kunde, Dietmar [3 ]
机构
[1] Airbus Def & Space GmbH, Dept Operat Anal & Studies, Claude Dornier Str, D-88090 Immenstaad, Germany
[2] Army Concepts & Capabil Dev Ctr, Div I, OR M&S Sect, Bruehler Str 300, D-50968 Cologne, Germany
[3] German Army Headquarters, von Hardenberg Kaserne Protzeler Chaussee 25, D-15344 Strausberg, Germany
关键词
D O I
10.1109/WSC57314.2022.10015234
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
To mimic a realistic representation of military operations, serious combat simulations require sound tactical behavior from modeled entities. Therefore, one must define combat tactics, doctrines, rules of engagement, and concepts of operation. Reinforcement learning has been proven to generate a broad range of tactical actions within the behavioral boundaries of the involved entities. In a multi-agent ground combat scenario, this paper demonstrates how our artificial intelligence (AI) application develops strategies and provides orders to subsidiary units while conducting missions accordingly. We propose a combined approach where human knowledge and responsibility collaborate with an AI system. To communicate on a common level, the orders and actions imposed by AI are given in natural language. This empowers the human operator to act in a human-on-the-loop role in order to validate and evaluate the reasoning of AI. This paper showcases the successful integration of natural language into the reinforcement learning process.
引用
收藏
页码:2082 / 2093
页数:12
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