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Using modeling and simulation and artificial intelligence to improve complex adaptive systems engineering
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作者 andreas tolk Philip Barry Steven C.Doskey 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2022年第2期70-90,共21页
Systems engineering practices are evolving to address fast-changing needs in fielding complex systems.These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by hu... Systems engineering practices are evolving to address fast-changing needs in fielding complex systems.These needs create an environment in which system needs evolve or change too quickly to be tracked or managed by humans’natural capabilities.We propose that systems engineering must aid systems engineering managers by providing architectural alternatives and design options.Further,as systems become more complex and dynamic,there is an increased need to identify hidden risks,model emergent behav-ior,and expose hidden patterns in the behavior of stakeholders.Systems engineering needs to evolve to build fast-fielded,resilient,and adaptive systems that leverage posi-tive reinforcement feedback loops with multiple experimental and real-world information sources.The very basis of systems engineering must evolve from today’s development paradigms to a future that leverages modeling,simulation,and artificial intelligence to drastically improve the capability and agility for developing new systems.This paper proposes a common way forward to enable this new form of complex adaptive systems engineering. 展开更多
关键词 Complex systems digital twin systems engineering
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