Abstract

In his article “On Mechanical Recognition” ([6]) R. J. Nelson brings to bear a branch of mathematical logic called automata theory on problems of artificial intelligence. Specifically he attacks the anti-mechanist claim that “[i]nasmuch as human recognition to a very great extent relies on context and on the ability to grasp wholes with some independence of the quality of the parts, even to fill in the missing parts on the basis of expectations, it follows that computers cannot in principle be programmed to recognize or learn to recognize all patterns” ([6]), p. 24). Nelson proposes, contrary to this claim, that “gestalt recognition is not beyond digital automata” ([6], p. 24). in particular, he claims, he will establish by what he calls “Turing machine arguments” ([6], p. 25) that the following four theses are true: (1)automata can recognize different pattern types in one and the same set of instances;(2)automata can recognize the “same” pattern in different (even completely disjoint) sets of instances;(3)automata can recognize incomplete, degraded patterns having missing or indeterminate parts;(4)automata can recognize family resemblances. ([6], pp. 24–25)

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