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The increasing role of automation in human-machine systems requires modelling approaches which are flexible enough to systematically express a large range of automation levels and assist the exploration of a large range of automation issues. A General Model of Mixed-Initiative Human-Machine Systems is described, along with a corresponding automation taxonomy, which: provides a framework for representing human-machine systems over a wide range of complexity; forms the basis of a dynamic, pseudo-mathematical simulation of complex interrelationships between situational and cognitive factors operating in dynamic function allocation decisions; and can guide methodical investigations into the implications of decisions regarding system automation levels.
Victor Riley (Sun,) studied this question.