This proposal is to develop a model-driven, agent-based Intelligent Toolset for Accessing Situational Knowledge (ITASK). This system will support Commanders and Battle Staffs in collecting and filtering data, from large information repositories in a net-centric environment, and in organizing and visualizing relevant portions to meet their critical situation awareness needs in a timely manner. We propose to use an integrated hybrid of intelligent search agents and decision support tools fitted to respond to knowledge management demands in the context of counterinsurgency planning and mission monitoring. Our approach focuses on enhancing performance in three areas: first, we will use decision models to identify critical information needs of the Battle Staff at any point in the decision making process; second, we will apply intelligent search agents to find and evaluate the information meeting those needs from the many large heterogeneous databases available; and finally, we will design a user interface with innovative display and retrieval technologies to allow rapid, efficient exploration of relevant information elements and to map them to related factors in the decision model. We will leverage our related developments in decision support systems for tactical users and prior focused research on multi-agent coordination and human interaction with intelligent systems.