Abstract
The paper discusses disparity issues in sensing tasks involving the production of a ‘high-level’ signal from ‘low-level’ signal sources. It introduces an abstraction theory which helps to explain the nature of the problem and point the way to a solution. It proposes a solution based on the use of supervised adaptive methods drawn from artificial intelligence. Finally, it describes a set of empirical experiments which were carried out to evaluate the efficacy of the method.
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