Valued situation information in IBSM
Kenneth J. Hintz, Steven Darcy · 2017
Situation information and sensor information are differentiated and a method for computing the situation information expected value (SIEV) is presented for use in Information Based Sensor Management (IBSM). Nine case pairs are evaluated in which the sensor capabilities vary among poor, average, and good sensors, and the goal lattice values vary among attack, defend, and stealth modes showing that the choice of the situation information request which maximizes the SIEV depends not only on the Bayes net representation of the situation, but also the context in which the sensing platform finds itself. Furthermore, the maximum SIEV for these 9 case pairs is shown to exceed the mean value of all the managed nodes by an average of 3.4. This feature makes it a useful statistic for determining the managed evidence node to select which produces the desired best next information collection opportunity. This paper is a further definition and refinement of the SIEV-net concept introduced in earlier papers including a method for explicitly computing the Situation Information Value.