  In recent years, Unmanned Aerial Vehicles (UAVs) have been used in fields
such as architecture, business delivery, military and civilian theaters, and
many others. With increased applications comes the increased demand for
advanced algorithms for resource allocation and energy management. As is well
known, game theory and machine learning are two powerful tools already widely
used in the wireless communication field and there are numerous surveys of game
theory and machine learning usage in wireless communication. Existing surveys
however focus either on game theory or machine learning and due to this fact,
the current article surveys both game-theoretic and machine learning algorithms
for use by UAVs in Wireless Communication Networks (U-WCNs). We also discuss
how to combine game theory and machine learning for solving problems in U-WCNs
and identify several future research directions.
