Agent-Based Model for Proportionality Assessment in Military Operations

Abstract

The proportionality assessment is a fundamental principle and a critical consideration in military operations. It involves weighing the anticipated military advantage of a military action against the potential for collateral damage, ensuring that the harm inflicted on civilians and civilian objects is not excessive in relation to the intended military gains. This process is inherently complex, requiring decision-makers to navigate uncertain and dynamic operational environments while integrating diverse variables, such as the operational context, available intelligence, and the evolving nature of conflict. To explore and better understand this decision-making process, this research introduces a novel Agent-Based Model (ABM) designed specifically to model and simulate proportionality assessment in military operations. The model proposed captures the interactions between decision-makers, environmental variables, and operational factors, providing a dynamic platform for analysing complex proportionality scenarios. By modelling these interactions and the underlying behaviour of this assessment process, this Artificial Intelligence (AI) model enables the simulation of diverse operational contexts, offering valuable insights into the decision-making process. Through this approach, this research contributes to the ongoing development of responsible and trustworthy AI models that enhance the understanding and evaluation of proportionality in military operations, supporting the creation of more informed and ethical operational strategies.