Real-time autonomy is a key element for system which closes the loop between observation, interpretation, planning, and action, commonly found in UxV, robotics, smart vehicle technologies, automated industrial machineries, and autonomic computing. Real-time autonomic cyber system requires timely and accurate decision making and adaptive planning. Autonomic decision making understands its own state and the perceived state of its environment. It is capable of anticipating changes and future states and projecting the effects of actions into future states. Understanding of current state and the knowledge/model of the world are needed for extrapolating actions and deriving action plans. This position paper proposes a hybrid, statistical-formal approach toward achieving realtime autonomy.
