Abstract: Aerial vehicles are assigned to routes within a transportation network based on a state of charge, state of power, and/or state of health for the aerial vehicle. Such aspects can be modeled based on one or more statistical models and/or machine-learned models, among other examples. As another example, an energy budget is used to ensure that the state of charge, state of power, and/or state of health of the aerial vehicle during and/or after traveling the route remains within the energy budget. A payload is assigned to a route and an associated aerial vehicle, thereby generating an itinerary. In examples, the itinerary is validated by the aerial vehicle to ensure that the aerial vehicle is capable of traveling the route with the payload. In examples where the aerial vehicle rejects the itinerary, the itinerary is assigned to another aerial vehicle and a new itinerary is identified for the aerial vehicle.

Abstract: A system that suggests recipients for a target document based on similarity of document data is provided. The system receives an indication of the target document. The system identifies documents that are similar to the target document based on a comparison of document data of the target document to document data of documents in a corpus of documents. The system then identifies entities associated with the identified documents. The system then suggests that one or more of the identified entities be considered as recipients for the target document. The system may also suggest recipients based on a recipient query. When a response to a prompt for a recipient does not match an entity in an address store, the system identifies an entity to suggest by using the response as a recipient query to identify an entity that matches the recipient query.