The performance of human operators significantly shapes the capabilities of the entire BMDS. Simulations of warfighter performance can benefit from incorporating real-world variations in operator proficiency, timeliness, creativity, fatigue or morale. Modeling Human-in-Control actions will increase the credibility of such simulations, which can be used in Performance Assessment, Futuristic Concept Analyses, Ground Tests, and Training, Exercises and Wargames. To address this, IAI and its collaborator, University of Michigan, have been awarded a contract entitled “Human-In-Control (HIC) Modeling and Integration Framework for BMDS Simulations.” An innovative HIC software modeling and integration framework will be built around objectively quantified cognitive models of human operators. These include the Executive-Process/Interactive Control (EPIC) and the GOMS (Goal Operator Method and Selection rules) Language Evaluation and Analysis (GLEAN). The framework provides the ability to model existing or futuristic operator workstations, which is used as declarative knowledge to develop high & low-fidelity cognitive models. It supports operator modeling of varying proficiency by allowing users to define task-specific timeline distributions, while the decisions are driven by fixed perceptual, cognitive, motor processor parameters and constraints. The cognitive model can interact with external decision models to determine the quantitative value of the outcome of certain motor tasks, so that meaningful simulation events can be generated for other BMDS simulation elements and components. A proposed HLA framework to interface with perceptual signal and motor actions declared in the HIC model provides an integration layer and a middleware to manage simulation time, and seeds to repeatable stochastic behavior external to the HIC model. Finally, a proposed enterprise service with scenario planning capability, to configure a simulation event from a repository of operator and workstation models, will support training and BMDS Performance Assessment.