Transfer of control skill by machine learning

Abstract Controlling complex dynamic systems requires skills that operators often cannot completely describe, but can demonstrate. This paper is concerned with the problem of transfer of human control skill into an automatic controller. The process of reconstructing a skill from an operator’s behavioural traces by means of Machine Learning (ML) techniques is called behavioural cloning. The paper gives a review of ML techniques applied to behavioural cloning, a number of representative experiments, and an assessment of the results. Some recent work is discussed, including a way of combining skill from several operators.