Streamlined AI architecture for wargaming

被引:0
|
作者
Rose, Melanie A. [1 ]
Ryer, Shaun M. [1 ]
机构
[1] Air Force Res Lab, Informat Directorate, 525 Brooks Rd, Rome, NY 13441 USA
关键词
Reinforcement Learning; Wargaming;
D O I
10.1117/12.3012668
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Legatus AI, an Air Force program supporting joint and coalition partners, is addressing the need for the creation of a common architecture of software and hardware for campaign level planning to empower the efficient development of AI and core AI capabilities. Building off lessons learned in previous command and control programs, Legatus AI seeks to close the capability gap by transforming AI development from non-reusable boutique solutions to an ecosystem of modular and reusable processes for configuring, training, evaluating, and deploying reinforcement learning and game theory agents for planning and wargaming environments. The prototype architecture added reinforcement learning capabilities to StreamlinedML to allow for communication between AI agents and games using a Docker-based solution. The architecture was tested on the Airlift Challenge simulation to ensure intended functionality and demonstrate the initial capability. Future work will incorporate additional agents and Unity-based wargames. The maturation of this architecture is a key cornerstone for future collaborative research and development of adaptable AI and plug-and-play wargaming platforms.
引用
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页数:8
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