scholarly journals Combat process simulation and attrition forecasting based on system dynamics and Multi-agent modeling

2022 ◽  
Vol 187 ◽  
pp. 115976
Author(s):  
Bo Peng ◽  
Shuo Liu ◽  
Lei Xu ◽  
Zhen He
2020 ◽  
Author(s):  
BO PENG ◽  
Shuo Liu ◽  
Lei Xu ◽  
Zhen He

Abstract Purpose: To predict and analyze the spatial and temporal distribution of combat attrition.Methods: Construct a combat process simulation and combat attrition forecasting model using system dynamics methods and introduce macroscopic attrition data to the attrition forecast model by using agents to decompose the attrition data, assigning battle wound information according to specific ratios.Results: Using the attrition forecast model, based on system dynamics, the causal loop and stock-flow relationship of the combat operation process may be constructed by combining the specific combat mission with an analysis of the factors that influence the operation, such as the lethality of the weapons and the defensive capability of the two sides. The damage levels of the various targets on the two sides in combat are converted into attrition data. Based on these data, an agent modeling method is used to extract the macroscopic attrition data derived from the battle attrition forecast model. By constructing a correspondence between the combat target damage level and the various types of battle injuries, the injury to each casualty may be modeled and assigned a value in order to complete the mapping from attrition to injury.Conclusions: This work establishes an attrition forecasting model based on system dynamics and an agent-based simulation model for the occurrence of casualties. It can estimate the temporal and spatial distribution of attrition in combat.


Author(s):  
R. Keith Sawyer

Sociology should be the foundational science of social emergence. But to date, sociologists have neglected emergence, and studies of emergence are more common within microeconomics. Moving forward, I argue that a science of social emergence requires two advances beyond current approaches—and that sociology is better positioned than economics to make these advances. First, consistent with existing critiques of microeconomics, I argue that we need a more sophisticated representation of individual agents. Second, I argue that multi-agent models need a more sophisticated representation of interaction processes. The agent communication languages currently used by multi-agent systems researchers are not appropriate for modeling human societies. I conclude by arguing that the scientific study of interaction and emergence will have to migrate out of microeconomics and become a part of sociology. Sociologists, for their part, should embrace multi-agent modeling to pursue a more rigorous study of these traditional sociological issues.


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