Target value assessment is a critical component of operational decision-making; however, existing methodologies suffer from the rigidity of static models in dynamic battlefield environments and the scarcity of specialized domain-specific data. To address these problems, we propose DECIS, a framework for adaptive decision support based on Retrieval-Augmented Generation (RAG). DECIS operates through a cohesive three-stage architecture centered on two core functions: first, RAG is employed to intelligently match optimal assessment strategies to dynamic contexts, thereby mitigating the challenge of limited military corpora; second, the Large Language Model (LLM) component autonomously generates... More >