Figure 2a shows the labeled satelli

Figure 2a shows the labeled satellite imagery spanning the geographic area of our targets’ regular daily activities. A single target of interest in the network has multiple frequent locations of interest, and a tendency to transition from those locations based on time of day. These locations are determined to be the target’s place of work (A), residence (B), and 3 places for social gathering (C,D,E). The darkened paths indicate the usual paths taken between the locations of interest. Figures 3a and b represent the social network around the target, and the fifirst order information about the location conditioned on time, respectively. The location distribution during the weekdays business hours has a very low entropy. Assuming the target’s place of work is unaffifiliated with criminal behavior, this target may be considered a criminal with a day job. Figure 3b shows a Markov chain governing the targets locational transitioning given that it is a weekday evening and ‘Work Group 2’ members are in Location C. There are a number of interesting problems that may be formulated, given this scenario. We start by describing the scenario in terms of the HBML representation framework.