Details of Grant 

EPSRC Reference:	GR/K63733/01
Title:	PART 11 OF COMPARISION OF DATA-DRIVEN METHODS OF MODELLING REAL-TIME CONTROL SKILLS
Principal Investigator:	Muggleton, Professor S
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Department:	Computer Science
Organisation:	University of Oxford
Scheme:	Standard Research (Pre-FEC)
Starts:	01 July 1995	Ends:	31 December 1995	Value (£):	21,103
EPSRC Research Topic Classifications:	Fundamentals of Computing
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Summary on Grant Application Form
Behavioural Cloning (BC) is a recently demonstrated use of Machine Learning for extracting executable models of human control skills from recorded performance data. When tested on new trials of the same task such computer-executed clones regularly outperform the human data source from which they were constructed. In particular, Michie and Camacho's use of BC to construct an autopilot able to fly simple missions with a simulated F16 combat aircraft has strongly confirmed this effect.This introduces a new requirement for supplementing existing methods of validating models of control generated by statistical and logical induction. Previously validation has been confined to the purely static tests of a model's predictivity on new data drawn from the same source as the training set. When the data is descriptive of human expert performance the quality of a model assessed by this static predictive methodology very seriously under estimates its quality when assessed against criteria of real-time performance. Our hypothesis is that although predictive validation is an under-estimate of the operational quality of induced rules it will prove to be a consistent under-estimate, showing sufficient correlation with real-time performance to be usable as a guide during the inductive design of real-time controllers by the BC method.
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