Abstract
Controlling complex dynamic systems requires skills that operators often cannot completely describe but can demonstrate. Behavioural cloning is the process of reconstructing a skill from an operator’s behavioural traces by means of Machine Learning techniques. In this paper we analyse various phenomena and problems observed in experiments in behavioural cloning in several domains: piloting, driving a container crane, production scheduling and pole-balancing. The analysis includes the “clean-up” effect and the time delay between state and action. We derive from this analysis some elements of an emerging methodology for behavioural cloning.
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