LDRD project final report : hybrid AI/cognitive tactical behavior framework for LVC.

Djordjevich, Donna D. ; Xavier, Patrick Gordon ; Brannon, Nathan Gregory ; Hart, Brian E. ; Hart, Derek H. ; Little, Charles Quentin ; Oppel, Fred John III ; Linebarger, John Michael ; Parker, Eric Paul

Sandia National Laboratories

关键词: Computer Architecture;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;    Robots;    Parallel Processing;    Planning;   

DOI  :  10.2172/1034891
RP-ID  :  SAND2011-9468
RP-ID  :  AC04-94AL85000
RP-ID  :  1034891

美国|英语

来源: UNT Digital Library

【 摘 要 】

This Lab-Directed Research and Development (LDRD) sought to develop technology that enhances scenario construction speed, entity behavior robustness, and scalability in Live-Virtual-Constructive (LVC) simulation. We investigated issues in both simulation architecture and behavior modeling. We developed path-planning technology that improves the ability to express intent in the planning task while still permitting an efficient search algorithm. An LVC simulation demonstrated how this enables 'one-click' layout of squad tactical paths, as well as dynamic re-planning for simulated squads and for real and simulated mobile robots. We identified human response latencies that can be exploited in parallel/distributed architectures. We did an experimental study to determine where parallelization would be productive in Umbra-based force-on-force (FOF) simulations. We developed and implemented a data-driven simulation composition approach that solves entity class hierarchy issues and supports assurance of simulation fairness. Finally, we proposed a flexible framework to enable integration of multiple behavior modeling components that model working memory phenomena with different degrees of sophistication.