Responding to Illegal Activities Along the Canadian Coastlines Using Reinforcement Learning

摘要

Machine learning (ML) algorithms can prove to be instrumental in certain complex ill-con-ditioned systems when inserted as a middle layer to interface low-level hardware, such as sensors and actuators, and high-level decision-making kernels. Such an interface provides a secondary, or supervisory, conditioning layer that would enhance the system's robustness in the face of various types of uncertainties and disturbances. This article elaborates how ML can leverage the solution of a contemporary problem related to the security of maritime domains.