Multi-Agent System for Courses of Action Comparison in Military Operations

Abstract

In military operations, decision-making often involves evaluating multiple Courses of Action (COA) under conditions of uncertainty and complexity, requiring robust tools to support planners in this critical process. On this behalf, this research introduces a Multi-Agent System (MAS) that integrates the Fuzzy Analytic Hierarchy Process (fuzzy-AHP) method for CoA comparison, providing a dynamic and distributed approach to decision-making. The system models the decision environment through interacting autonomous agents, each representing decision-makers, operational variables, and contextual factors. By incorporating Fuzzy-AHP, the system combines the structured framework of Analytic Hierarchy Process (AHP) with the uncertainty handling capabilities of fuzzy logic, enabling agents to collaboratively evaluate hierarchical decision criteria. These criteria include key technological and operational factors, assessed using fuzzy representations of expert judgments and uncertain parameters. This approach facilitates an intelligent, nuanced, and adaptive comparisons of CoA, ensuring flexibility and consistency in multi-criteria scenarios. Experimental results demonstrate that the proposed MAS model not only enhances the accuracy and interpretability of COA evaluations, but also adapts effectively to changing operational conditions, providing actionable and trustworthy insights. This work contributes to advancing Artificial Intelligence (AI)-based military decision-support tools for military operations, addressing the complexities of CoA evaluation in dynamic and uncertain environments.