In the included work the Unmanned Aerial Vehicle (UAV) mission is represented by energy graphs motivated by the analysis in . The problem of the shortest path routing is revisited when a dynamically changing environment is considered. It is assumed that information about the map is received while on flight due to events. In addition, UAVs are required, while on mission, to "scout" areas of interest which involves extracting as much intelligence as possible and traversing it in the most safe flyable means. Hence, the UAV should be capable of integrating knowledge from a variety of sources and re-plan its mission accordingly in order to fulfil objectives. Motivated by the previous, depending on the decision making process, the notion of a "temporary" optimum path can be of physical and functional sense. The problem is modeled as a multistage decision making process, where each stage is triggered by an event and is characterized by a current starting point, an area for reconnaissance purposes and a final destination. Hence, given the current availability between paths, the objective is to devise a policy that leads from an origin or current known location to a destination node while traversing the unknown region of interest with the minimal energy demand
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