Robust Adaptive Markov Decision Processes: Planning with Model Uncertainty

Abstract

The ability of autonomous systems to make complex decisions is becoming an increasingly commonplace requirement for many cooperative control operations, including the management of teams of robots such as unmanned aerial vehicles (UAV). Central to this research is the requirement to optimize the vehicle decisions, such as route planning and allocation of team resources, while operating in a dynamic and uncertain environment. Even with the advent of increasingly sophisticated vehicle sensors that can improve the information about the surroundings, uncertainty remains a ubiquitous feature of UAV applications and a key issue in UAV research.