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Lockheed Martin has been a premier builder and developer of manned aircraft and fighter jets since 1909. Since then, aircraft design has drastically evolved in many areas including the evolution of manual linkages to fly-by-wire systems, and mechanical gauges to glass cockpits. Lockheed Martin's knowledge of manned aircraft has produced a variety of Unmanned Aerial Vehicles (UAVs) based on size/wingspan, ranging from a micro-UAV (MicroStar) to a hand-launched UAV (Desert Hawk) and up to larger platforms such as the DarkStar. Their control systems vary anywhere between remotely piloted to fully autonomous systems. Remotely piloted control is equivalent to full human involvement with an operator controlling all the decisions of the aircraft. Similarly, fully autonomous operations describe a situation that has the human having minimal contact with the platform. Flight path control relies on a set of waypoints for the vehicle to fly through. This is the most common mode of UAV navigation, and GPS has made this form of navigation practical.

This chapter focuses on networks comprised of explicit data sources and information and non-human machines as actors. As non-human actors, we include intelligent agents, robotics, and other forms of interactive artificial intelligence. All six facets of knowledge networks are explored. Given these networks’ peculiar nature, three facets have particular importance, including geography, topology, and relationships. The authors provide profiles of seven networks, including semantic and citation networks, webpage networks, communications and computer networks, and energy grids.